Embedded learning and optimization for the next generation of smart industrial control systems





ESR8 – EPFL

PhD Position in Embedded Learning and Predictive Control






 

Institution:
École Polytechnique Fédérale de Lausanne, Switzerland






 
 
Content:
  1. Introduction
  2. PhD Project Description
  3. Supervisors and Main Contacts
  4. Candidate Profiles
  5. Application
  6. Marie Curie Eligibility Criteria In Short






Introduction
 
The PhD position is part of the European Training Network ‟ELO-X – Embedded Learning and Optimization for the neXt generation of smart industrial control systems”. ELO-X will recruit altogether 15 PhD fellows at 6 research universities and 5 international companies from 5 European countries, who will meet regularly during exchange visits, training events, workshops, and summer schools organized by the network.
 
The position at the EPFL lies at the intersection of control, learning theory and practical mathematical optimization and will be based in the Automatic Control Lab (Laboratoire d’Automatique) headed by Colin Jones. The aim is the development of advanced optimization methods and open-source software for learning-based control and their application to industrially relevant control problems. While these methods are generic and applicable in several branches of engineering, they shall be tested and used in close cooperation with the other ELO-X PhD fellows, in particular with those who are based in Siemens, ETH Zurich, Mitsubishi Electric Research Laboratory and Freiburg – during mutual exchange visits of several months duration.
 
PhD Project Description
 
PhD Project: Embedded Learning and Predictive Control.

Bringing adaptive and learning-based control, coupled with advanced optimization tools for planning, predictive control and estimation to embedded platforms promises ease of design and deployment, as well as improved performance for a broad range of application areas. There are, however, a large number of challenges to overcome before such data-driven control methods are commonplace. This project will focus on a key area: computational methods for the deployment of real-time embedded predictive control based on data-driven and adaptive models.

 

The specific direction of the research project will be developed in collaboration with the PhD fellow, but two exciting and indicative directions are:

  • Development of predictive control and moving horizon estimation approaches arising from recent work in Koopman operator theory leading to convex optimization problems for data-driven non-linear models. The potential is for extremely fast data-driven control from data.
  • Real-time embedded optimization approaches handling the extreme non-convexity arising when using predictive models based on robust kernel learning and/or deep kernel learning for MPC. The potential here is to go from data to reliable, safety-first control of highly complex nonlinear systems.

The project will involve a mix of control theory, machine learning, numerical optimization, software development and practical expertise. A key output of the project will be open-source software building on the group’s development of the polyMPC tool.

 

In addition, practical studies will be undertaken both utilizing and informing the fellow’s research in collaboration both with other researchers in the lab, as well as with ELO-X partners through secondments.



Timeline and remuneration:

The ideal start time is spring or early summer 2021. The PhD project will last for three to four years, and will be carried out at the Automatic Control Lab at the EPFL. The PhD years include at least one longer visit – a so called “secondment” – between one and six months to another group in the ELO-X network, depending on the project needs and the scientific interests of the PhD fellow. The first year is mainly dedicated to studying and getting acquainted with the relevant state of the art in optimization and learning for control, as well as the development of a research plan based on the goals and interests of the fellow in tight collaboration with the supervisor. The following years will be spent executing the plan with a focus on the topics described above.

A fourth PhD year can be added and funds are reserved for this at the EPFL. The remuneration is generous and will be in line with the EC rules for Marie Curie grant holders augmented to a level equal to a standard EPFL PhD student. See the website here for details: Salary and conditions for EPFL doctoral students
 
 
Supervisors and Main Contacts
 
Supervising team at EPFL:
 

The student will work in a collaborative environment and will join a tight-knit team with a wide expertise in control, optimization and computational methods. A positive attitude and ability to work with others is a necessity for this position. Prof. Colin Jones, the head of the Automatic Control Lab, will supervise the project and work closely with the applicant.

 
Main Contacts at ELO-X Partner Groups which could host secondments:
 
  • Siemens Industry Software: Dr Herman Van der Auweraer (robotic driving);
  • ETH Zurich: Prof. Melanie Zeilinger (gaussian processes);
  • Freiburg University: Prof. Moritz Diehl (embedded sparse solvers);
  • Mitsubishi Electric Research Laboratories: Dr. Rien Quirynen (embedded optimization applications)

 

Candidate Profile
 

The ideal candidate will have a master degree in control systems and / or optimization, solid programming skills and an interest in developing both novel theory, as well as practical tools. Outstanding students with only a partial match to this list are encouraged to apply. Proficiency in English is a requirement.

All positions adhere to the European policy of balanced ethnicity, age and gender. Both men and women are encouraged to apply.
 
Application
 
To apply, send an email to elo-x@imtek.uni-freiburg.de in form of one single PDF attachment containing all contents or links (any other information within the email will not be processed). Subject of your email should be: “ELO-X PhD Application – ESR 8”.

Please include, in your single PDF document, the following items in this order:

 

  1. A cover letter incl. statement of research interests and career goals (max. 2 pages);
  2. An academic CV;
  3. Contact details of at least two referees incl. phone numbers and emails;
  4. Your diplomas and transcript of course work and grades;
  5. Sample of technical writing (publication or thesis);
  6. Proof of English language proficiency test results.
 

Please send your application before January 17, 2021.

 

Note that your PDF will be forwarded to several people in the ELO-X institutions and that in particular all Supervisory Board members of ELO-X will have access to your application material. If you want to apply to more than one ELO-X position, please create and send separate PDFs.

 

Please note that the selected applicant will also need to apply and be accepted by the EPFL doctoral school. The process for this will be discussed during the interviews.
 
 
Marie Curie Fellowship Eligibility Criteria in Short
 
To be eligible, you need to be an “early stage researcher” i.e. simultaneously fulfill the following criteria at the time of recruitment:
  1. Nationality: you may be of any nationality.
  2. Mobility: you must not have resided or carried out your main activity (work, studies, etc…) in Switzerland for more than 12 months in the 3 years immediately prior to your recruitment under the ELO-X project.
  3. Qualifications and research experience: you must be in the first 4 years of your research career after the master degree was awarded.