Control-oriented information selection

Fields:

Automatic Control, sensor fusion, optimization

Profile:

A highly motivated and talented individual is sought to join the team as a research collaborator. The successful candidate should have a solid background in control. Knowledge about numerical optimization or machine learning, with a strong experience in computational methods and algorithm development is appreciated. The candidate must have a proven track record of research excellence, demonstrated by publications in top-tier journals and/or conferences.
Candidates having a doctoral degree will be preferred. They should have 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 in the field of control, with the aim to develop a novel framework allowing systems distributed over wireless communication networks (e.g., 5G or 6G) to optimally select only the relevant information sources for the given control task.

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:

€ 29.185,24 per year

Duration:

1 year

SSD:

IINF-04/A Systems and Control Engineering

Project:

PRIN 2022 dal titolo “Too much Information! Control-Oriented Dynamic Information Selection” codice MUR 2022NLTTBN, CUP: D53C24003690006, Codice UGOV P0363