Job description

The Uncertainty in Artificial Intelligence (UAI) group is a quickly growing group embedded in the Data and AI (DAI) cluster at the Eindhoven University of Technology (https://dai.win.tue.nl). In the DAI cluster, we aim at developing foundations of AI for the present and the future. This includes the design of new AI methods, development of AI algorithms and tools with a view at expanding the reach of AI and its generalization abilities. In particular, we study foundational issues of robustness, safety, trust, reliability, tractability, scalability, interpretability and explainability of AI.
The UAI group is looking for a highly motivated and skilled Ph D candidate to work in the area of Causality. The concrete research direction will be determined together with the successful candidate. The research topics include, but are not restricted to:

• Causality: Theory and Application.
• Causal Probabilistic Circuits.
• Causal Representation Learning.
• Causal Explanations.
• Causality and Large Language Models.
• Counterfactual learning.

Job requirements

• Master’s degree in Computer Science, Mathematics, or a related field.
• Excellent analytical skills.
• Excellent coding skills (e.g. Python, Py Torch, Tensorflow).
• Excellent academic writing and presentation skills.
• Proficiency in English (written and spoken).
• Desire to conduct excellent research and publish in high quality conferences and journals.
• Independent thinker and self-responsibility.
• Ability and desire to collaborate and work in teams.
• Ability and desire to support teaching and to co-supervise bachelor and master students.

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 Ph D 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 assistant professor dr. Devendra Singh Dhami, email d.s.dhami@tue.nl.
Visit our website for more information about the application process or the conditions of employment. You can also contact HR Services, email HRServices.MCS@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:

• A research statement, including research experience and interests, and a short outline of the preferred future research direction (max. 1 page).
• A CV, including education history, relevant courses and theses, research experience (if available), a list of publications (if available), and teaching experience (if available).
• Transcript of records for Bachelor’s and Master’s degrees.
• Electronic copy of (or a link to) Master thesis.
• Electronic copy of publications (if available; if more than 3, please submit top 3). If no publications are available, please submit some substitute, e.g. presentations slides of a given presentation.
• Contact details of or recommendation letters from 2 referees.

After the initial selection, the invited candidates will be given a task that they are expected to complete in 2 weeks. The task will be sent in early December and the interviews are expected to take place on 20.12.2024.
We look forward to receiving your application and will screen it as soon as possible.
The position may be filled early if a suitable candidate is found, so do not wait until near the deadline to apply. Applications are only accepted via the dedicated web system (do not send applications via email).