DC3. Conceptualization and development of a novel personalized AI-based therapy support system to guide the therapy in conjunction with the therapist

DC3. Conceptualization and development of a novel personalized AI-based therapy support system to guide the therapy in conjunction with the therapist

GOAL: working on the conceptualization of a system for suggesting personalized therapy actions and parameters, or their adjustments executed by the system in collaboration with the therapist. Based on the current state of the patient (assessed by DC2/DC9) in the context of the therapy process, at any given time the system should be able to evaluate whether any therapy action is necessary, and if so, compile a list of possible actions to address the challenge, suggesting an optimal plan.

REQUIRED PROFILE: MSc in Computer science, biomedical engineering, artificial intelligence, electrical engineering, rehabilitation engineering. The MSc degree should be obtained by May 2025.

DESIRABLE SKILLS: Algorithm design, machine learning, decision-making systems, signal processing, data analysis, experience with robotic or therapeutic systems, programming (e.g., Python, MATLAB, C++), knowledge of clinical therapy processes, interdisciplinary collaboration, communication skills, understanding of therapist-patient interaction dynamics, optimization techniques.

HOST: DC3 will be affiliated with UT and CSIC, and will perform two research visits (FSL and ETH) along the project. This DC is linked to the RT2 of TAILOR project.

DEADLINE for applications: February 1, 2025 .

SUPERVISORS: Edwin van Asseldonk (UT), Eduardo Rocon (CSIC)

SECONDMENT HOSTS: Federica Tamburella (FSL), Peter Wolf (ETH)