PhD student on Time Perception in AI

iMEC

Belgium

July 9, 2021

Description

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 unique.

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. Main tasks:

  • 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 conferences
  • 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 administrative matters.
  • 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 experiments.
  • 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).
  • Interested?

    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 pieter.simoens@ugent.be.

    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