Computational methods for active learning of dynamical models and model predictive control

Titolo in italiano: “Metodi computazionali per l’apprendimento attivo di modelli dinamici e il controllo predittivo”

1 Post Doctoral Fellow position
(Deadline September 6th, 2024 13:00 )
Fields

 

Model predictive control, system identification, numerical optimization, machine learning, design of experiments

Activity

 

Carry out research activities within the scope of the ERC Advanced Grant “COMPACT” (COmputational Model Predictive and Adaptive Control Tools) on one of the following topics: active learning methods for designing system identification experiments coupled with robust MPC schemes for safe data collection; numerical optimization methods for offline nonlinear system identification and online model adaptation; preference-based MPC calibration algorithms based on human calibrators’ preferences, possibly in a game-theoretic setting; explicit and semi-explicit MPC algorithms for fast online controller evaluation and light MPC adaptation schemes. Co-supervision of laboratory activities to validate the research results on an experimental robotic platform.

Profile

 

A highly motivated and talented individual to join our team as a Postdoctoral Researcher. The successful candidate should hold a PhD in one of the following fields: model predictive control, numerical optimization, system identification, or machine learning, with a strong background in computational methods and algorithm development. The candidate must have a proven track record of research excellence demonstrated by publications in top-tier journals and conferences, experience with numerical optimization techniques and/or system identification/machine learning approaches, very good programming skills in relevant languages for scientific computing (e.g., Python, Julia, MATLAB), and the ability to work independently and as part of a team.

Formal requirements

 

  • PhD in one of the following fields: model predictive control, numerical optimization, system identification, machine learning;
  • Excellent knowledge of both written and spoken English.
Duration

 

2 years, renewable

Gross amount

 

40.530,00 €/year

SSD

 

IINF-04/A – Systems and Control Engineering

IINF-04/A - Automatica

Project

 

progetto “COmputational Model Predictive and Adaptive Control Tools” – COMPACT, GA n. 101141351, che è stato finanziato nell’ambito del bando Call for ERC Advanced Grant: ERC-2023 ADG rivolto alla ricerca di frontiera e valutato secondo il criterio dell’eccellenza

Job Research Area: 
CSSE
Job Research Unit: 
DYSCO
Job Contract Type: 
Assegno di ricerca
Full call

 

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Selection procedure and criteria

Selection procedure conditions are transparent and are based on international standards.

Procedure

A Selection Committee, appointed by the Director, assesses all applications on the basis online application info and - if provided - reference letters.Shortlisted candidates, selected on the basis of the preliminary analysis, are invited for a research presentation at IMT. Travel expenses to Lucca for theresearch presentation interview will not be reimbursed.

Selection Criteria

The evaluation criteria are based on: Quality of research activity, including publications in peer-reviewed journals and references; Research organization experience and participation in international/national research projects and research periods in public and private institutions (academic and non-academic);Relevance of the candidate's profile for the development of IMT's research activities; Teaching, mentoring and supervision experience; Motivation; Excellent knowledge of English, both written and spoken; As well as any other requirements as specified in the advertisement.

Application

Apply ONLINE only.

Before starting prepare the application attachments and information as listed below.

Info

  • Personal info and contact info (compulsory)
  • Number of your Identity Document (Passport or Identity Card) (compulsory)
  • University degree (compulsory) and Ph.D. (obtained, or "ongoing")
  • Name, position, institution and email address of three referees (compulsory)
  • An email, with the appropriate instructions to upload the reference letters will be automatically generated and sent to your referees.

Attachments

  • Your CV in English (compulsory);
  • One research paper (published or working paper): compulsory.
    Shortlisted candidates will be asked to present this research paper in the final stage of the selection.
Contacts: