Careers/Jobs

Following is a list of available positions announced in the most recent issue of Eletter. Listings in previous issues of Eletter can be found here.



7.1. PhD: Imperial College London, UK
Contributed by: Thulasi Mylvaganam, thulasi.mylvaganam06@imperial.ac.uk

PhD Studentship in Nonlinear Control

Applications are invited for a PhD studentship on distributed control for nonlinear systems within the Department of Aeronautics, Imperial College London.

Distributed systems are ubiquitous: teams of (aerial) robots, wind farms or dynamic sensor networks are just a few examples. Designing controllers for such systems is an important topic within control theory. To increase the autonomy of distributed systems it is crucial to develop novel methods for efficient and effective cooperative, distributed control.

The goal of the PhD studentship is to develop novel methods for designing distributed controllers for general, nonlinear systems, which include multi-agent systems such as teams of (aerial) robots. The developed methods will be based on a rigorous system theoretic approach typical of control systems. The student will therefore be required to gain familiarity and expertise in several topics within and related to control systems theory (including nonlinear control theory, linear algebra, optimization, game theory etc.)

Imperial College is consistently ranked as one of top universities in the world and top 3 universities within the UK. In 2016/17 Imperial ranked 9th in the world in the QS and 8th in the world in the THE rankings. It has been ranked as the most innovative university in Europe. Imperial staff and alumni include 15 Nobel laureates, 2 Fields Medalists, 70 Fellows of the Royal Society, 82 Fellows of the Royal Academy of Engineering and 78 Fellows of the Academy of Medical Sciences. The student will benefit from this dynamic environment and from the unique facilities offered by Imperial College London.

Applicants should have a keen interest and solid background in Control Engineering and Mathematics and have experience with using MATLAB. Knowledge of Nonlinear Control is preferable.
Applications are invited from candidates with (or who expect to gain) a first-class honours degree or an equivalent degree in Engineering, Mathematics or a related discipline (for more details, see https://www.imperial.ac.uk/study/pg/apply/requirements/pgacademic/).

“Funding is available for UK citizens and EU citizens. The studentship is for 3.5 years starting as soon as possible and will provide full coverage of tuition fees and a tax-free stipend.”

Applications will be assessed as received and all applicants should follow the standard College application procedure (http://www3.imperial.ac.uk/pgprospectus/howtoapply).

Informal enquiries and requests for additional information for this post can be made to: Dr Thulasi Mylvaganam via email: thulasi.mylvaganam06@imperial.ac.uk.

To apply, please go to http://www.imperial.ac.uk/study/pg/apply/how-to-apply/
Any queries regarding the application process should be directed to Ms Lisa Kelly by email at l.kelly@imperial.ac.uk.

Closing date for applications: Open until filled
Start Date: As soon as possible

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7.2. PhD: CNES and CRAN, France
Contributed by: Marion Gilson, marion.gilson@univ-lorraine.fr

PhD CNES and CRAN (CNRS, Université de Lorraine, Nancy)
SYSTEM IDENTIFICATION FOR ATTITUDE CONTROL OF SATELLITES

Description
The validation of the attitude control algorithms uses high fidelity simulators with the most accurate possible models of satellite dynamics and orbital environment. Some parameters of these models are nevertheless difficult to identify on ground (disturbing torques amplitude, satellite inertia, flexible modes characteristics), or are submitted to large uncertainties. To get more accurate numerical values, flight telemetry can be used, but the identification process is complex due to physical characteristics of the measurements (low sampling rate, noise, bias etc) and due to operational constraints: the necessary attitude profiles allowing the observability of the parameters cannot always be performed (out of flight envelop profiles, or mission interruption required). In some other more critical cases, accurate identification of the parameters is a pre-requisite for the attitude control feasibility: for example, on very low altitude orbits a small knowledge error on the position of the center of mass can lead to a non-optimal guidance profile, with respect to aerodynamic disturbances and to the loss of the satellite due to actuator saturations. Finally, on elliptic orbit with very low perigee, the disturbing torques change rapidly and it would be interesting to compute a time-variant control law adapting to amplitude and frequency changes of the disturbances in satellite frame. To this aim, one needs to identify time-varying models.

From a theoretical point of view, accurate parametric identification of “grey box” models, the search of optimal inputs (for excitation signals generation) and time-varying parameters model identifications are topics of great interest in academic research, also with more and more numerous industrial applications. A lot of methodological and numerical tools exist that can better meet the requirements.

The PhD objectives are to develop new closed-loop identification techniques for time-varying parameters, either for the validation of attitude control laws with more accurate models of the satellite dynamics and environment or for adaptive control laws design.

The foreseen tasks are the following:
1. Closed-loop recursive identification of time-varying parameter grey box models by using telemetry: design of new algorithms and comparison to existing ones (Kalman filters for example). This problem raises several open questions, as the choice of nonlinear functions for domains where the physical behavior is more difficult to know. This choice is often the result of a trade-off between model flexibility and parsimony. Model flexibility allows the model to include complex nonlinear phenomena, whereas parsimony aims at using the minimum number of parameters to model these nonlinear phenomena. Once this choice is done, the relevant parametric estimation method must be developed and the (in-) validation of the obtained model performed. Besides, some critical aspects of grey box identification will be studied: identifiability and sensitivity analysis of physical parameters, robustness of the proposed algorithms to initial conditions or measurement noise, or computation of uncertainty regions for the estimated parameters.
2. Input signal selection: as the model can be accurately identified only if the input/output data contain enough information, the selection of suitable excitation inputs for identification of closed-loop and time-varying system is an important issue.
Implementation and validation of the new approach with real flight telemetry, and comparison with existing tools

Desired profile
Master in automatic control

The PhD program period is 3 years, starting early 2017.
Closing date for applications
20.01.2017

Structure description
Host Laboratory : Centre de Recherche en Automatique de Nancy (CRAN)
Lab Promotors : Marion GILSON - marion.gilson@univ-lorraine.fr, Hugues GARNIER - hugues.garnier@univ-lorraine.fr
CNES Promotor : Christelle PITTET - christelle.pittet@cnes.fr

Requests for further information should be sent to marion.gilson@univ-lorraine.fr and christelle.pittet@cnes.fr and include:
1. Covering/Motivation letter
2. Curriculum Vitae
3. Contact details of two academic referees.

Website: https://cct.cnes.fr/system/files/these_identif_SCAO_0.pdf

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7.3. PhD: Eindhoven University of Technology, The Netherlands
Contributed by: Roland Toth, r.toth@tue.nl

Phd Position: Eindhoven University of Technology, The Netherlands
Contributed by: Roland Toth, r.toth@tue.nl

Two Phd Positions are available at the Control Systems Group of the Eindhoven University of Technology, The Netherlands:

PhD position #1: AUTOMATED SYSTEMATIC LPV MODELING
PhD position #2: SYSTEM ORIENTED LPV CONTROL DESIGN

Project description:

Linear Parameter-Varying (LPV) systems are flexible mathematical models capable of representing Nonlinear (NL)/Time-Varying (TV) dynamical behaviors of complex physical systems (e.g., wafer scanners, car engines, chemical reactors), often encountered in engineering, via a linear structure. The LPV framework provides computationally efficient and robust approaches to synthesize digital controllers that can ensure desired operation of such systems - making it attractive to (i) high-tech mechatronic, (ii) automotive and (iii) chemical-process applications. Such a framework is important to meet with the increasing operational demands of systems in these industrial sectors and to realize future technological targets. However, recent studies have shown that, to fully exploit the potential of the LPV framework, a number of limiting factors of the underlying theory ask a for serious innovation, as currently it is not understood how to (1) automate exact and low-complexity LPV modeling of real-world applications and how to refine uncertain aspects of these models efficiently by the help of measured data, (2) incorporate control objectives directly into modeling and to develop model reduction approaches for control, and (3) how to see modeling & control synthesis as a unified, closed-loop system synthesis approach directly oriented for the underlying NL/TV system. Furthermore, due to the increasingly cyber-physical nature of applications, (4) control synthesis is needed in a plug & play fashion, where if sub-systems are modified or exchanged, then the control design and the model of the whole system are only incrementally updated. This project aims to surmount Challenges (1)-(4) by establishing an innovative revolution of the LPV framework supported by a software suite and extensive empirical studies on real-world industrial applications; with a potential of technological innovation in the high-impact industrial sectors (i)-(iii).

The PhD positions are within the scope of the APROCS (Automated Linear Parameter-Varying Modeling and Control Synthesis for Nonlinear Complex Systems) initiative funded by the European Research Council (ERC) and it aims to overcome the fundamental limitations of the current LPV framework listed by Challenges (1)-(4).

Phd project #1 focuses on automated systematic LPV modeling to develop (1) systematic tools for converting first-principle models of complex dynamical systems, described by nonlinear/time-varying ODE’s and PDE’s, to low complexity, but exact LPV descriptions, (2) in case of unknown dynamical relations, complete the resulting models by powerful data-driven techniques building on the fusion of system identification and machine learning methods, (3) achieve control / objective oriented embedding of the dynamics of the to be modeled system together with simulation relation based verification methods, (4) achieve incremental modeling with plug & play properties.

Phd project #2  focuses on system oriented LPV control design to develop a (1) radical paradigm-shift based LPV control design framework, where the control synthesis focuses on the resulting controlled behavior (open or closed loop) with the targeted physical system, providing directly a NL/TV controller, i.e., the LPV concept is used as a solution approach for the underlying optimization problem. This requires the development of (2) novel stability and performance concepts and corresponding synthesis techniques with also an (3) objective of achieving incremental synthesis with plug & play properties.

Candidate profile:
* strong background in systems and control, mathematics (complex functional analysis, abstract algebra), statistics (for position #1), signal processing and electrical machines or mechanical engineering.
* solid programming skills in C++, DSpace, Mathematica and/or Matlab
* good communicative skills, and the attitude to partake successfully in the work of a research team.
* good command of the English language (knowledge of Dutch is not required).
* should have completed, or about to complete, a Bachelors/Masters/Honours degree in Systems and Control, Electrical Eng., Mech. Eng. or related areas

Starting date (intended):
1 September, 2017

Please send a complete CV as well as your motivation letter and transcripts to dr. R. Toth (r.toth@tue.nl) with a subject of "Phd position.”

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7.4. PhD: University of the Armed Forces Munich, Germany
Contributed by: Gunther Reissig, gunther2014@reiszig.de

PhD position: Formal methods in control (Munich, Germany)

University of the Armed Forces Munich, Germany
Department of Aerospace Engineering
Institute of Control Engineering

We invite applications for a doctoral researcher position in the field of formal methods in control. The successful candidate is expected to advance theory of as well as computational methods for abstraction-based controller synthesis, to a degree that facilitates routine, fully automated, practical application of the approach to nonlinear continuous-state plants and complex specifications. The focus is on synthesis algorithms that are both efficient and formally correct.

The project involves theoretical work, algorithm and software development, and, on a small scale, experimental work. There is no teaching requirement and no coursework to be completed. Competitive salary is offered according to the tariff ``TVOeD Bund, E 13''.

Required qualifications:
* MSc degree (or equivalent, giving access to doctoral studies) in Electrical Engineering, Mathematics, Computer Science, or a related field. Students about to complete their MSc will also be considered.
* Excellent academic record, showing a strong theoretical/mathematical background and a strong interest in dynamical systems.
* Proficiency in programming (C or Ada/SPARK).
* Excellent communication skills in English (CEFR level C1).

In addition, experience in one of the following fields would be a plus: Set-valued or validated numerics; dynamic programming; formal methods in control; reactive synthesis; professional-grade software development.

Your complete application consists of the following documents, which should be sent as a single PDF file to the email address given below (deadline: Feb 15, 2016):
* CV with photo
* One-page cover letter (clearly indicating available start date as well as relevant qualifications, experience and motivation)
* University certificates and transcripts (both BSc and MSc degrees)
* Contact details of up to three referees
* Possibly an English language certificate and a list of publications

All documents should be in English, with the exception of university certificates and transcripts, which may also be in German. The position is open to applicants worldwide; no special security clearance necessary.

Priv.-Doz. Dr. habil. Gunther Reissig
http://www.reiszig.de/gunther/
Email: gunther2014@reiszig.de, Subject: PhD ref 1077

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7.5. PhD: Southern Illinois University, USA
Contributed by: Arash Komaee, akomaee@siu.edu

We are searching for a PhD student to work on a funded research assistant position in the Department of Electrical and Computer Engineering at Southern Illinois University (SIU), Carbondale, IL, USA. The position is available for Fall 2017 and contingent on satisfactory performance and fulfillment of the department requirements can be extended to the duration of study.

The position is in the general area of dynamical systems and control with an emphasis on magnetic control of micro-robots. Applicants with a BS degree in mechanical or aerospace engineering are preferred but those with a background in electrical engineering are also considered. A relevant MS degree is a definite advantage. Applicants must demonstrate strong courage for independent experimental work in the lab, in addition to interest in theory development.

Interested applicants are invited to send their application or inquiries to Dr. Arash Komaee at akomaee@siu.edu. A complete application package includes a Curriculum Vitae, name and contact information of three references, a brief description of the applicant's research interests, GRE score, and TOEFL/IELTS score for international applicants.

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7.6. PhD: Lehigh University, USA
Contributed by: Eugenio Schuster, schuster@lehigh.edu

PhD Positions in Modeling and Control of Distributed Parameter Systems

Two fully funded PhD positions in the general area of Control Systems are available within the Laboratory for Control of Complex Physical Systems in the Department of Mechanical Engineering and Mechanics at Lehigh University. PhD candidates should have an undergraduate, or preferably a Masters degree, in engineering, physics or applied math. A solid mathematical and physical background is required together with a broad education in control systems. Some demonstrated research experience is a plus. The candidates should be interested in doing research in the general area of modeling and control of distributed parameter systems with applications to magnetohydrodynamic flows and plasmas.

Lehigh University, founded in 1865, is located in Bethlehem, Pennsylvania, 50 miles north of Philadelphia and 75 miles southwest of New York City. It offers an inspiring academic environment, excellent education, state-of-the-art research and computer facilities, very competitive economic conditions (tuitions, stipend, housing, health insurance) for graduate students, and great career opportunities after graduation. More information can be found at http://www1.lehigh.edu/academics/graduate.

Candidates interested in being part of this educational and research opportunity are encouraged to send by e-mail their Curriculum Vitae to Prof. Eugenio Schuster at schuster@lehigh.edu.

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7.7. PostDoc: The Ohio State University, USA
Contributed by: Mingjun Zhang, zhang.4882@osu.edu

PostDoc: The Ohio State University, Columbus, OH.

We have a funded two-year post-doc position to work on optimal control for a bio-inspired autonomous underwater vehicle (AUV). The AUV has been built and tested for underwater exploration using a simple closed-loop control. We are interested in developing advanced optimal control algorithm for energy-efficient propulsion, and have been investigating new theoretical optimal control methods to integrate hydrodynamics and feedback control for energy-efficient trajectory tracking.

Candidates with background in mathematics and theoretical control are highly encouraged to apply.

Please send your CV to Mingjun Zhang: zhang.4882@osu.edu

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7.8. PostDoc: I3S Laboratory, France
Contributed by: Maria João Rendas, rendas@i3s.unice.fr

A post-doc position (for 6 months, possibly extended for a longer period) at the I3S Laboratory at Sophia Antipolis (France) is opened, to work on the development of modelling tools for early detection of abnormal athletic dynamic evolutions. The study is carried in close collaboration with an International Sports Federation, and will build on a large database of past and ongoing performance of top-ranking athletes.

The candidate should have strong competences in statistical machine learning and modelling and is expected to develop the associated software tools (in Matlab in the development phase).

The position is available immediately and the application will stay open until a suitable candidate is found.

Applications (including CV and a cover letter of motivation) should be sent to rendas@i3s.unice.fr and pronzato@i3s.unice.fr. Applicants willing to have additional information are invited to contact us directly by email.

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7.9. PostDoc: Eindhoven University of Technology, The Netherlands
Contributed by: Roland Toth, r.toth@tue.nl

Postdoc Position: Eindhoven University of Technology, The Netherlands

A postdoctoral position is available at the Control Systems Group of the Eindhoven University of Technology, The Netherlands:

Linear Parameter-Varying (LPV) systems are flexible mathematical models capable of representing Nonlinear (NL)/Time-Varying (TV) dynamical behaviors of complex physical systems (e.g., wafer scanners, car engines, chemical reactors), often encountered in engineering, via a linear structure. The LPV framework provides computationally efficient and robust approaches to synthesize digital controllers that can ensure desired operation of such systems - making it attractive to (i) high-tech mechatronic, (ii) automotive and (iii) chemical-process applications. Such a framework is important to meet with the increasing operational demands of systems in these industrial sectors and to realize future technological targets. However, recent studies have shown that, to fully exploit the potential of the LPV framework, a number of limiting factors of the underlying theory ask a for serious innovation, as currently it is not understood how to (1) automate exact and low-complexity LPV modeling of real-world applications and how to refine uncertain aspects of these models efficiently by the help of measured data, (2) incorporate control objectives directly into modeling and to develop model reduction approaches for control, and (3) how to see modeling & control synthesis as a unified, closed-loop system synthesis approach directly oriented for the underlying NL/TV system. Furthermore, due to the increasingly cyber-physical nature of applications, (4) control synthesis is needed in a plug & play fashion, where if sub-systems are modified or exchanged, then the control design and the model of the whole system are only incrementally updated. This project aims to surmount Challenges (1)-(4) by establishing an innovative revolution of the LPV framework supported by a software suite and extensive empirical studies on real-world industrial applications; with a potential of technological innovation in the high-impact industrial sectors (i)-(iii).

The position is within the scope of the APROCS (Automated Linear Parameter-Varying Modeling and Control Synthesis for Nonlinear Complex Systems) initiative funded by the European Research Council (ERC) and it aims to overcome the fundamental limitations of the current LPV framework listed by Challenges (1)-(4).

This 3 years Postdoc position focuses on model reduction approaches to be developed both in the time and frequency domain that aim at complexity reduction of converted LPV first-principle models by balancing the trade-off between complexity and accuracy in terms of the control/user objectives. This concept of reduction is drastically different from the available literature and require fundamentally new concepts to take into account: (1) the true underlying behavior of the represented NL/TV system, (2) how closed-loop measures of control performance effect the trade-offs and (3) how to achieve joint state-order and scheduling complexity reduction which represent two complementary sources of complexity. A thorough (4) understanding of LPV models in the frequency domain is also intended to be developed. This challenging objective would allow the generalization of powerful design concepts of controller tuning and performance specifications together with stability results and model reduction methods in the LTI case to the LPV case.

Candidate profile:
* strong background in systems and control, mathematics (complex functional analysis, abstract algebra), signal processing and electrical machines or mechanical engineering.
* solid programming skills in C++, DSpace, Mathematica and/or Matlab
* good communicative skills, and the attitude to partake successfully in the work of a research team.
* good command of the English language (knowledge of Dutch is not required).
* should have completed, or about to complete, a PhD degree in Systems and Control

Starting date (intended):
1 September, 2017

Please send a complete CV as well as your motivation letter and transcripts to dr. R. Toth (r.toth@tue.nl) with a subject of "Postdoc position.”

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7.10. PostDoc: Clemson University
Contributed by: Human Resources, none@given.com

Clemson University: College of Engineering, Computing and Applied Sciences: Automotive Engineering
Post Doctoral Fellow - Automotive Engineering

Location: 4 Research Drive, Greenville, SC 29607

The ideal candidate will work in a highly engaging research environment together with other faculty and graduate students. He/She will conduct the research with the PI – including both theory and experiments (30%), will assist with student advising (10%), will write technical reports and papers (25%), present research results (5%), and help manage the battery lab (10%), and help with proposal writing (20%).

QUALIFICATIONS
PhD degree (or are about to graduate) in mechanical, electrical aerospace engineering, applied mathematics or statistics. Demonstrated proficiency with writing technical research papers

APPLICATION INSTRUCTIONS
To submit your application, please upload an updated CV with a list of publications via Interfolio. Questions should be directed to Prof. Onori (sonori@clemson.edu). Review of applications will continue until the position is filled. Only shortlisted candidate will be contacted via email.

Clemson University is an AA/EEO employer and does not discriminate against any person or group on the basis of age, color, disability, gender, pregnancy, national origin, race, religion, sexual orientation, veteran status or genetic information. Clemson University is building a culturally diverse faculty and staff committed to working in a multicultural environment and encourages applications from minorities and women.

Apply Here: http://www.Click2Apply.net/b92dhw7kt7

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7.11. PostDoc: Washington University in St. Louis, USA
Contributed by: ShiNung Ching, shinung@wustl.edu

Postdoctoral Opening: Optimal Control of Neural Activity

Postdoctoral positions are available at Washington University in St. Louis in the area of control and optimization with applications in brain dynamics. This position is a part of an NIH BRAIN initiative-funded project on stimulation protocols for neuron-level control.

Current neurostimulation technologies provide substantial capability to manipulate the activity in neuronal networks. However, several key challenges remain, including handling many degrees of freedom with (usually) only a few stimulating actuators. This project will involve the development and implementation of optimal control methods for the precise manipulation of neuronal activity at the level of neurons and networks thereof. Candidates should have a strong background in the general areas of systems theory, control engineering, machine learning and/or optimization. Prior experience in neuroscience is not needed, but a general interest/curiosity about brain dynamics is a plus!

This project will be jointly supervised by Profs. ShiNung Ching and Jr-Shin Li in the Department of Electrical and Systems Engineering at Washington University. Interested applicants should send a CV and brief description of interests and goals to (shinung@wustl.edu) and (jsli@wustl.edu). Applications will be evaluated as soon as they are received, until the positions are filled.

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7.12. PostDoc: University of Illinois, USA
Contributed by: Naira Hovakimyan, nhovakim@illinois.edu

We are seeking an outstanding post-doctoral researcher to join the Advanced Controls Research Lab at Mechanical Science and Engineering of University of Illinois. The candidate is expected to be an exceptional team player with strong background in mathematics and deep interest in applications. The work will be focused on optimization, robust control and machine learning. He/she will need to work with interdisciplinary group of students, publish rigorously and provide support for development of research program.

To apply for the position, please send an email to nhovakim@illinois.edu, summarizing your interest and your CV, including at least three references.

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7.13. PostDoc: Grenoble University, France
Contributed by: Christophe Prieur, christophe.prieur@gipsa-lab.fr

Postdoc in signal processing and estimation of the magnetic heading, at Grenoble University, France.

This work will be conducted in collaboration between an academic lab (Gipsa) and the SYSNAV company. The candidat should have a PhD in signal processing (filtering, estimation) or control theory (observers, nonlinear dynamics).

See
http://www.gipsa-lab.grenoble-inp.fr/~christophe.prieur/Offers/postdoc1.pdf
for more information on this position.

Advisors: Nicolas Le Bihan and Christophe Prieur
Salary: 2025 euros/month after taxes (gross: 2515 euros).
Dates: beginning: Sept. or Oct 2017, for one year. The position may be closed before if a competent candidate has applied.

How to apply: Applications should be declared before the 1st of June and include a detailed resume, the CV and a list of (at least) two references to one of the advisors

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7.14. PostDoc: Inria, France
Contributed by: Andrey POLYAKOV, andrey.polyakov@inria.fr

Postdoc Position in Automatic Control (Inria, Lille, France)

Research Topic:
Control problems for separated turbulent flow are of great interest in the view of many modern challenges. For example, aerodynamic losses are believed to be one of the main source of energy wastage for a vehicle at speeds higher than 50km/h. According to the existing ecological estimates, the reduction of these losses at 25% will decrease pollutions for more than $10^7$ tonnes of $CO_2$ per year. Optimization of the vehicles shapes is one of possible solution for reducing aerodynamic losses (or drag) caused by the turbulence related mechanisms such as flow separation on the vehicle. When the incoming flow is unsteady, active control strategies become important. Postdoc research is devoted to a design of feasible control algorithms for separated (turbulent) flows.

Applicants must have PhD degree (or equivalent) in Applied Mathematics (with experience in automatic control) or in Control Engineering (with good mathematical skills)

How to apply?
Please do send (before 1 May 2017) your CV, list of publications and a motivation letter to Andrey Polyakov (andrey.polyakov@inria.fr) or Jean-Pierre Richard (jean-pierre.richard@ec-lille.fr).  We will contact you no later 15 June 2017 if your application will be accepted.

Duration : 12 months (possibly 18 months)
Starting date of the contract : autumn 2017
Salary: approx. 2 600 euros brut

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7.15. Research Fellow: Delta-NTU Corporate Laboratory, Singapore
Contributed by: Lihua Xie, ELHXIE@ntu.edu.sg

Job Title: Research Fellow
Delta-NTU Corporate Laboratory for Cyber-Physical Systems
School of Electrical & Electronic Engineering

Job Description:
The project is concerned with vehicle navigation and target tracking with collision avoidance in cluttered environments for automatic guided vehicle (AGV). Such AGVs rely on a variety of sensors (e.g. LiDAR, UWB, IR and/or camera) in order to navigate safely in dynamic and cluttered indoor environments. The main goal is to develop reliable and accurate sensing systems and algorithms for detection, tracking and classification of both moving and stationary obstacles in the vicinity of a moving unmanned vehicle.

Working at Smart Manufacturing track of Delta-NTU Corporate Laboratory for Cyber-Physical Systems, the research fellow will be part of a large and world-leading research team in networked control and autonomous systems. The research work will include sensing system and algorithm development, perception, system integration, simulations and testing for obstacle avoidance and navigation in cluttered environments. We aim to develop efficient and scalable algorithms to consolidate data from multiple heterogeneous sensors. These algorithms will allow us to detect and track targets more accurately by making full use of the information available from onboard sensors and sensors installed in environments.

Requirement:
1.Candidate must have a PhD degree in engineering.
2.Extensive research experiences in related fields: Sensor fusion, Indoor localization, Advanced control algorithm
3.Strong at signal processing and estimation, algorithms development and implementation, data modelling and perception.
4.Experiences in Simultaneous Localization and Mapping (SLAM).
5.Knowledge of wireless sensing and communication network.
6.Excellent team-work and communication skills, preferably with engineering project management experience.
7.Excellent problem formulation and problem solving skills.
8.Strong organizational skills to juggle multiple tasks within the constraints of timelines and budgets with business acumen.

Relevant experiences or skills in one or more of the following areas will be a plus:
1.Excellent programming skills in C/C++ and MATLAB.
2.Experiences in multi-sensor systems (e.g., electromechanical systems, actuators, sensors, control theory, autonomous systems, state machines) development.
3.Has patent or product development experience

Application Procedure:
Interested candidates please send your CV/resume to: Prof. Xie Lihua through E-mail: ELHXIE@ntu.edu.sg

Electronic submission of application is highly encouraged.
Only short-listed candidates will be notified for interview.
Application closes when the positions are filled.

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7.16. Research Fellow: University of Melbourne, Australia
Contributed by: Michael Cantoni, cantoni@unimelb.edu.au

Research Fellow Positions: University of Melbourne, Australia.

Two post-doctoral positions are available to work on systems and control theory research that is relevant to the automation of large-scale gravity-powered water distribution networks. The ideal candidate has a PhD in engineering or applied mathematics, and expertise in one or more of the following topics:
(i) Modelling, identification and feedback control of distributed-parameter systems;
(ii) Robust control with decentralized information;
(iii) Fault monitoring and performance analysis for large-scale systems;
(iv) Robust / stochastic MPC for constrained control in the presence of uncertainty;
(v) Structured and distributed computation for optimization; and/or
(vi) Hierarchical control and scheduling for dynamical systems.

Both positions are with the Department of Electrical and Electronic Engineering, for up to 24 months.

The closing date for applications is 10 March 2017.

For more details, including how to apply, search jobs.unimelb.edu.au for "systems and control" or "0042604".
http://jobs.unimelb.edu.au/caw/en/job/889885/research-fellow-in-systems-...

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7.17. Visiting Professor: LCCC Linnaeus Center, Sweden
Contributed by: Anders Rantzer, rantzer@control.lth.se

Visiting professor

The LCCC Linnaeus center - Lund Center for Control of Complex engineering systems - is announcing sabbatical support for visiting professors during 2017-18. The support covers accommodation and office space, plus a partial salary contribution. Please contact LCCC director Anders Rantzer <rantzer@control.lth.se> for further details.

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7.18. Faculty: University of Rhode Island, USA
Contributed by: Haibo He, he@ele.uri.edu

Faculty Position Announcement - Robotics

Tenure-Track Assistant Professor of Electrical Engineering
Department of Electrical, Computer, and Biomedical Engineering
University of Rhode Island
Kingston, RI, USA

Applications are invited for a tenure-track position in Electrical Engineering at the rank of Assistant Professor beginning in Fall 2017. We are particularly interested in candidates working in one or more areas of robotics including, but not limited to, industrial robots, mobile robots, or autonomous vehicles and drones, and who have some background in control theory. A doctorate in Electrical Engineering or closely related field is required at the time of appointment. The successful candidate will be expected to teach and develop undergraduate and graduate courses and establish a high-quality, externally-funded, research program.

The Department of Electrical, Computer and Biomedical Engineering offers programs leading to the BS, MS, and PhD degrees. The interdisciplinary nature of our Department will provide the new faculty member with opportunities to interact with a broad range of colleagues. A brand-new 195,000 square foot engineering building has recently been approved (construction to start in 2016) will provide an excellent environment for interdisciplinary research collaborations.

The University of Rhode Island is a comprehensive doctoral research, Land Grant, Sea Grant and Urban Grant University. URI College of Engineering offers innovative undergraduate and graduate programs, stresses links between diverse fields of inquiry, and values outreach, scholarship, and laboratory-based learning. The University of Rhode Island is a medium-sized public university located near the southeastern end of the state and picturesque New England. The main campus is located in Kingston, an established, family-friendly, small community only five miles from the Narragansett Bay and the Atlantic Ocean. Rhode Island’s proximity to the ocean moderates its weather compared to other New England States. The region offers excellent outdoor recreational activities, good public school systems, and ready access by car or public transportation to Providence, Boston, New Haven, and New York City metropolitan areas and airports.

Required Qualifications
1. An earned doctorate in electrical engineering or closely related field at the time of appointment.
2. Demonstrated record of scholarly activity in one or more areas of robotics, including, but not limited to, industrial robots, mobile robots, or autonomous vehicles and drones.
3. Demonstrated background in control systems.
4. Demonstrated ability to work with diverse groups.
5. Demonstrated proficiency in written communication skills.
6. Demonstrated proficiency in oral communication skills.

Preferred Qualifications
1. Demonstrated ability to teach undergraduate and graduate courses in robotics
2. Demonstrated ability to teach undergraduate and graduate courses in control theory.
3. Demonstrated ability to work in multi-disciplinary teams.
4. Demonstrated ability to develop an externally funded research program.

First consideration will be given to applications received by January 15, 2017. Second consideration may be given to applications received by February 15, 2017. The anticipated start date is August 2017, and salary is commensurate with qualifications and experience. Applicants should submit the following: (1) a cover letter; (2) a complete curriculum vitae including the full contact information for at least three professional references; (3) a narrative, limited to two pages, describing your research and how it relates to the required qualifications; (4) a narrative, limited to one page, describing your teaching background, philosophy, and preferences, including existing courses in our department and new courses you might develop. Submit applications on-line at https://jobs.uri.edu/postings/1921. Additional information is available at the URI Department of Electrical, Computer and Biomedical Engineering web site, www.ele.uri.edu. Questions about the position can be forwarded to the Chair of the Search Committee, Dr. Richard Vaccaro, vaccaro@ele.uri.edu.

We hope to attract applicants who can teach in a diverse University community and have demonstrated ability in helping students from diverse backgrounds succeed. We are committed to building a multicultural work force and strongly encourage women, racial/ethnic/gender minorities, persons with disabilities, and covered veterans to apply. The University of Rhode Island is an Equal Opportunity/Affirmative Action employer.

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7.19. Faculty: Washington University in St. Louis, USA
Contributed by: Hiro Mukai, facsearch@ese.wustl.edu

Tenured/Tenure-Track Faculty
Washington University in St. Louis
Electrical and Systems Engineering

The Preston M. Green Department of Electrical & Systems Engineering at Washington University in St. Louis invites applications for faculty positions at all levels, for fall 2017. The Electrical & Systems Engineering department enjoys a new building, Preston M. Green Hall, with state-of-the-art facilities. Candidates should be exceptionally strong, possess novel and creative visions of research, and commit gladly to teaching at both the undergraduate and graduate levels. They should have an earned doctorate in Electrical Engineering, Computer Science, Applied Physics, Systems Engineering, Mathematics, Statistics, Operations Research or related fields.

Technical areas of interest include, but are not limited to, applied physics, integrated circuits, nano devices, device packaging, imaging, signal processing, cyber-physical systems, control systems, operations research, optimization, applied mathematics, and applied statistics. Applications include biomedicine, robotics, financial engineering, and modeling of physical and complex systems. Successful candidates are expected to conduct high-quality research and teaching, publish in peer-reviewed journals, and participate in department and university service.

Applications will be accepted immediately, and interviews will begin after January 1, 2017. The details of the application process and necessary documents are found at the following site:
http://ese.wustl.edu/aboutthedepartment/Pages/faculty-openings.aspx

Washington University in St. Louis is a medium-size private university, which is 19th in the national university ranking and 14th in the undergraduate teaching ranking, both according to the U.S. News & World Report.

Washington University in St. Louis is an Equal Opportunity and Affirmative Action employer, and invites applications from all qualified candidates. Employment eligibility verification required upon employment.

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7.20. Faculty: Universite Grenoble Alpes, France
Contributed by: Christophe Prieur, christophe.prieur@gipsa-lab.fr

Associate Professor (maitre de conferences) position at Universite Grenoble Alpes, France, in Automatic Control department. For more information, please visit

https://t.co/Nm1bJFuSPh

Do not hesitate to contact the research and training contacts indicated in the previous link.
Apply on GALAXIE:
https://www.galaxie.enseignementsup-recherche.gouv.fr/ensup/cand_recrute...
before the 30th of March.

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7.21. Research Engineer/Scientist: AreteX Systems, USA
Contributed by: Behnood Gholami, bgholami@aretexeng.com

Research Engineer/Scientist: Signal Processing and Machine Learning

AreteX Systems, a medical technology startup company accelerating the use of information technology in healthcare, has an immediate opening for a Research Engineer/Scientist in its office located in the New York City area. The position involves developing signal processing and machine learning algorithms for innovative biomedical technologies. We are looking for a self-motivated, highly talented individual with an excellent background in control systems, signal processing, and machine learning. The successful candidate will work closely with a team of physicians, nurses, engineers, and scientists in designing new clinical decision support systems. Candidates with experience in the analysis of data generated by medical devices such as mechanical ventilators and hemodynamic monitors data will be given a higher priority.

Minimum Requirements:

- MS or PhD in electrical engineering, computer science, mechanical engineering, biomedical engineering, aerospace engineering, physics, applied mathematics, or a similar discipline.
- Experience in algorithm development for signal processing and machine learning applications.
- Solid understanding of machine learning techniques.
- Familiarity with signal processing concepts.
- Experience in Python.

Preferred Qualifications:

- Prior work in analyzing data from mechanical ventilators, hemodynamic monitors, and biosignals (EEG, EMG, ECG, accelerometer, ...).
- Prior work in robotics and/or mechatronic systems.
- Solid understanding of dynamical systems and control concepts.
 

 

Additional Resources:

IEEE JobSite

IEEE JobSite is a searchable database containing a comprehensive listing of jobs in the electrical, electronic, engineering, and computer-related fields. For listings specific to control systems, please see here 

IEEE resumeLab is an online service that allows IEEE members to develop a resume or CV. You can also perform mock interviews using over 900 potential interview questions. The information developed on IEEE ResumeLab is easily shared via a personalized website.
IEEE mentorCentre is an online program that facilitates the matching of IEEE members for the purpose of establishing a mentoring partnership.
IEEE collabrotec site: an integrated online community where technology professionals can network, collaborate, and create — all in one central hub. The IEEE Collabratec™ online community offers a suite of productivity tools and is available to technology professionals around the world with exclusive features for IEEE members.