[I-RIM ML] [Jobs] (Second posting) PhD Position: Learning Robot Manipulation/Mobility Policies that Facilitate Implant–driven Assistive Robot Control, KULeuven, Belgium

Renaud Detry kuleuven-c1-2022a at renaud-detry.net
Tue Jul 5 11:57:56 CEST 2022


PhD Position: Learning Robot Manipulation/Mobility Policies that Facilitate Implant–driven Assistive Robot Control, KULeuven, Belgium

Status: open

Location: KU Leuven, Leuven, Belgium
Starting Date: Summer/fall 2022
Duration: 4Y
Supervisor: Prof. Renaud Detry
Announcement Posted On: June 10 2022
Application Deadline: Open until filled
Status and additional information: https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=202207050958000296549&URLID=2&ESV=10.0.16.7295&IV=2F4049D58EFC9C1CC40588D89B0A8C39&TT=1657015082237&ESN=CKLYP1OBcLD5DEMJ3u4ZGbXGe61vMaVwMVdXP5Ix7W0%3D&KV=1536961729280&B64_ENCODED_URL=aHR0cDovL3JlbmF1ZC1kZXRyeS5uZXQvam9icy92YWMva3VsZXV2ZW4tYzEtMjAyMmEucGhw&HK=2DEDB2414DB339F94226E2A2E5DF2592C00A2E012845A9CC69411CA12DB720C2

# Research

KU Leuven looking for one highly motivated PhD student to study means of blending artificial robot control with neural-implant signals to allow tetraplegic/locked-in patients to regain mobility and manipulation autonomy. We will study means of inferring the patient's intent (e.g., intended hand motion) from measurements taken by a neural implant. The robot will blend neural trajectory data with contextual, computer-vision–derived attributes of the scene, such as the location of objects, to anticipate where/what the user intends to grasp, and pre-orient/pre-shape the hand accordingly. Complementarily, we will study means of letting the user assist its robot in tasks where autonomous decision-making is known to struggle. Our goal is to allow the user to execute tasks that are currently beyond the capabilities of purely-autonomous systems, at a fraction of the mental effort of a purely human-driven robot.

Funding is available for four years.

KU Leuven is Belgium's largest university, and a leading higher education and research institution – amongst the top-100 universities worldwide. It is located in Leuven, a short train hop away from Brussels. This project will be hosted by two departments: the departments of electrical engineering(group PSI) and mechanical engineering (group RAM).

# TA Work

The successful candidates will assist with teaching at most one EE/ME course per quad (i.e., two per year). The workload will be at most 6 hours per week.

# Requirements

The successful candidates must have a degree(s) in Engineering, Physics, Math, Computer Science or a related field, and fluency in at least one mainstream computer programming language.

Candidates must demonstrate their ability to assist with the TA work, either with a degree or transcripts of courses relevant to EE or ME.

A machine learning or computer vision background is strongly valued.

# Application

Applicants must submit:

• a one-page cover letter describing their background and interests,
• curriculum vitae, including publications, and a list of in-person or online courses on computer vision, machine learning and robotics that the applicant has completed,
• availability (earliest feasible starting date),
• if available, a link to the candidate's SCM page (e.g., on GitHub.com) that illustrates past programming projects,
• a copy of academic transcripts (bachelor/master grades).
Applicants must be prepared to provide two reference letters upon request.

Applications should be sent, *in a single PDF document*, to:

kuleuven-c1-2022a at renaud-detry.net

Questions can be directed to the same address.

Applications can be sent immediately and will be evaluated until June 15 2022. To verify if the position is still available, visit https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=202207050958000296549&URLID=1&ESV=10.0.16.7295&IV=E99DDDFE50CF2A7089F86827036E525D&TT=1657015082236&ESN=WjPJLjcxumfXBa6MuNpKYSjm4g9x9OF4hetaW5Lxqtg%3D&KV=1536961729280&B64_ENCODED_URL=aHR0cDovL3JlbmF1ZC1kZXRyeS5uZXQvam9icy92YWMva3VsZXV2ZW4tYzEtMjAyMmEucGhw&HK=4850CFD6AD7979C3D6401689975BED4D87F6A665398E9535866488FCBD416C6C.


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