PhD on Analysis of Bayesian Intelligent Autonomous Systems

PhD on Analysis of Bayesian Intelligent Autonomous Systems

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Position: PhD-student

Irène Curie Fellowship: No

Department(s): Electrical Engineering

FTE: 1.0

Date off: 29/09/2024

Reference number: V36.7665

Job description

Short Description

Are you interested in Artificial Intelligence systems that learn from interactions with their environments? Have you wondered what the best way to collect data is for them? How much information they gain by observing specific data points? Then this PhD position might be for you. We are looking for someone that is interested in uncovering information-theoretic properties of intelligent systems that learn from their environment.

Job Description

Not all data is equally useful. A major challenge in training artificially intelligent systems that learn from interactions with their environments (agents), is to acquire the most useful data points. For example, where should a robot look in order to pick up a cup? Active Inference is a framework for designing agents that balance information-seeking and goal-seeking behavior. This PhD position will dive into the information-theoretic basis of this framework.

You will work with probabilistic machine learning methods, such as (variational) Bayesian inference and Active Inference, applied to signal processing and control systems. We are looking for someone that has experience with information theory, i.e., someone who is familiar with concepts such as entropy, mutual information, and divergence measures. You will use this knowledge to derive insights into whether the data acquisition protocols for Active Inference agents can be improved.

You will become a member of the Bayesian Intelligent Autonomous Systems laboratory (https://biaslab.github.io/), which is part of the Signal Processing Systems group at the Electrical Engineering department. We are a close team of over a dozen researchers that work on probabilistic models, inference algorithms, and signal processing/control system applications. We are known for our probabilistic programming toolbox RxInfer.jl (https://rxinfer.ml/) and our foundational perspective on Artificial Intelligence (https://youtu.be/2wnJ6E6rQsU?si=UYgNxU5LeFd1Nq6P).

Job requirements

  • A master’s degree (or equivalent university degree) in Electrical Engineering, Mathematics, Computer Science, or Physics.
  • A curious and research-oriented attitude.
  • Ability to work in an interdisciplinary team.
  • Motivated to develop your teaching skills and coach students.
  • Fluent in spoken and written English (C1 level).

Conditions of employment

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:

  • Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale P (min. €2,770 max. €3,539).
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care, and sports facilities.
  • An allowance for commuting, working from home, and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.

Information and application

About us

Eindhoven University of Technology is an internationally top-ranking university in the Netherlands that combines scientific curiosity with a hands-on attitude. Our spirit of collaboration translates into an open culture and a top-five position in collaborating with advanced industries. Fundamental knowledge enables us to design solutions for the highly complex problems of today and tomorrow.

Curious to hear more about what it’s like as a PhD candidate at TU/e? Please view the video.

Information

Do you recognize yourself in this profile and would you like to know more?
Please contact the hiring manager Wouter Kouw, Assistant Professor, w.m.kouw@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact Hamdi Joudeh, Associate Professor, h.joudeh@tue.nl.

Are you inspired and would like to know more about working at TU/e? Please visit our career page.

Application

We invite you to submit a complete application by using the apply button. The application should include a:

  • Cover letter in which you describe your motivation and qualifications for the position.
  • A proof of proficiency in English and academic writing (e.g., MSc thesis, or scientific paper).
  • Curriculum vitae, including a list of your publications and the contact information of three references.
  • Copies of diplomas with course grades (transcripts).

We look forward to receiving your application and will screen it as soon as possible. The vacancy will remain open until the position is filled.

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