Ghent University Distributed Machine Learning- imec IDLab Research Group
IDLab is a research group of Ghent University, as well as a core research
group of imec. IDLab performs fundamental and applied research on data science
and internet technology, and counts over 300 researchers. IDLab is also part
of imec, the world-leading research and innovation hub in nanoelectronics and
digital technologies. The combination of our widely acclaimed leadership in
microchip technology and profound software and ICT expertise is what makes us
This position is within the research group Distributed Machine Learning. This
group focuses on innovative machine learning techniques in situations where
intelligence is divided between multiple entities, be it multiple robots, edge
device and cloud-backend, or human-AI interaction. This position is situated
in the latter domain, and will be carried out within the context of a
prestigious FET project.
What you will do
Time perception is key to many human cognitive abilities such as planning on
different time scales, decision making, communication and effective
cooperation. Despite this importance, humans do not possess a dedicated organ
for tracking physical time. Instead, time perception is a remarkable
subjective time experience, with well-described but complex deviations between
reported times and objective clock time. Sometimes time feels compressed
(time flies), whereas at other moments time feels expanded, depending on the
environment, the task at hand, allocation attention, etc.
This plasticity of time perception raises the question whether time perception
can modulated. This objective will be pursued within the EU H2020 project
“ChronoPilot – Modulating Human Subjective Time Experience” in collaboration
with five project partners.
The goal of this project is to modulate the time perception by presenting
well-targeted visual, auditory and haptic sensations by means of VR/AR, haptic
vests, environmental sounds, nearby humans and robots, etc. Such technology
can lead to more efficient shared workspaces.
The PhD student accepted for this position will be responsible for developing
computational models of human subjective time, and for a decision model that
decides when and how to generate multisensory stimuli.
Design, development, and implementation of a computational model of
subjective time experience. These models take as input environmental
stimuli, task-related stimuli as well as the affective state, and output a
subjective time estimation.
Extension of this model to a decision model for the generation of
multisensory stimuli, also in the context of multi-person settings.
Validation of these models through user experiments, and interpretation of
the results in tight collaboration with psychologists.
Integration of these models into a working prototype, in cooperation with
other technical partners.
Close international and interdisciplinary collaboration (especially
psychology) with project partners from Germany, Greece, and Luxembourg
Independent work on a diverse set of tools and methods (e.g., machine
learning, multi-robot simulations and experiments with hardware, VR/AR)
Collaboration on publications and presentations at international
Supervision of master theses related to the subject of this PhD
What we do for you
We offer a fully funded PhD scholarship for a maximal period of 4 years (upon
positive progress evaluation). The PhD research is fundamental and
innovative, but with clear practical applications. You will join a young and
enthusiastic team of researchers, post-docs and professors. The PhD position
is immediately available.
Who you are
You have a degree in Master of Science/Engineering, preferably in computer
science, computational neuroscience or cognitive science. To be admissible
to the PhD-program, your degree must be equivalent to 5 years of
engineering studies (bachelor + master) in the European Union.
You have a solid academic track record (graduation cum laude or grades in
the top 10%). Please do not hesitate to contact us regarding these
You have proven knowledge of machine learning.
You have a strong interest in one or more of the following domains:
cognitive modelling, computational neuroscience, Bayesian machine
learning. Proven experience in one of these domains, e.g. via your master
thesis topic or projects, is a plus (but not a necessity).
Besides computational modelling, you are willing to engage in hands-on
implementation and prototyping to develop proof-of-concepts.
You are interested in working with other researchers in a
multidisciplinary setting, in particular with psychologists to set-up user
You speak and write English fluently (C1 CEFR level).
You have good communication skills.
You are eligible for a Flemish PhD scholarship (i.e., you have not
enjoyed such a scholarship before).
Apply with motivation letter, scientific resume, abstract of your master
thesis, diplomas and detailed academic results (courses and grades),
relevant publications, and at least one reference contact. This information,
as well as possible questions, must be sent to Prof. Pieter Simoens at
After the first screening, suitable candidates will be invited for an
interview (also possible via teleconference). This interview is the first
stage of a multi-stage application procedure. Applications will be screened as
soon as they are received. The position is open until the vacancy is filled.
Tentative starting data: Sept-Nov 2021