Robust Model Predictive Control for Autonomous Driving Applications

Fields:

Model predictive control, autonomous driving, set-theoretic methods, optimization, optimal control

Profile:

A highly motivated and talented individual is sought to join the team as a research collaborator. The successful candidate should have a background in model predictive control, optimal control, set-theoretic methods, autonomous driving or numerical optimization, with a strong experience 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/or conferences.
Candidates having completed at least two years of a doctoral program will be preferred. They should have experience with numerical optimization techniques, very good programming skills in relevant scientific computing languages (e.g., Python, Julia), and the ability to work both independently and as part of a team.

Activity:

The researcher will carry out research activities aiming at developing novel robust MPC techniques for autonomous driving.

Formal requirements:

• Master's degree or equivalent in mathematics, artificial intelligence, engineering, or related fields;
• enrollment in a doctoral program;
• excellent English both written and spoken.

Gross amount:

€ 19.367,00 per year

Duration:

1 year

SSD:

IINF-04/A Systems and Control Engineering

Project:

1) IMT generale 

2) progetto dal titolo “Assimilazione di dati epidemiologici e controllo ottimo per previsioni a breve termine e gestione dell’emergenza COVID-19 in Italia”, Acronimo: EPIDOC, FISR2020IP_04249 – CUP: D65F21000290001, identificato in contabilità interna dal codice UGOV: P0203