Titolo in italiano: “Metodi computazionali per l’apprendimento attivo di modelli dinamici e il controllo predittivo”
Model predictive control, system identification, numerical optimization, machine learning, design of experiments
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.
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.
- PhD in one of the following fields: model predictive control, numerical optimization, system identification, machine learning;
- Excellent knowledge of both written and spoken English.
2 years, renewable
40.530,00 €/year
IINF-04/A – Systems and Control Engineering
IINF-04/A - Automatica
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
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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.