PhD-TA on safe reinforcement learning in partially observable settings

Job description

Position

We are looking for an enthusiastic PhD-TA candidate to work on advancing the field of sequential decision making under partial observations, with a particular focus on safe reinforcement learning methodologies. The primary objective is to build AI agents that, given a limited number of sensors, can operate safely in an unknown environment. The project focuses on the development of novel methods that can learn models of the world dedicated to safety. Such a model may be built based on the experiences of the agent or historical data collected by a different agent.

Program

During your PhD, you will have the opportunity to tackle challenging problems related to the use of memory, feature extraction, and representation learning.  You will delve deeply into the rapidly evolving field of reinforcement learning, while also exploring relevant areas of machine learning.

Group

You will work on the Data and AI cluster, where you will have the chance to collaborate with experts designing new AI methods, algorithms and tools to expand the reach of AI and its generalization abilities, focusing particularly on the foundational issues of robustness and safety. The cluster offers a inclusive and collaborative workspace with numerous opportunities for social interactions.

Application and Supervision

The position is available from December 1st and will be performed under the supervision of Dr. Thiago D. Simão (httpss://tdsimao.github.io).

Job requirements

• A master's degree (or an equivalent university degree) in Computer Science, Mathematics, Physics, or related discipline.
• Experience with decision-making frameworks (MDP, POMDP, bandits, dynamical systems, etc).
• Experience in programming and empirical analysis in machine learning (Python, PyTorch, etc).
• Excellent problem-solving skills and ability to work independently and collaboratively.
• Strong written and oral communication skills in English.
• Motivated to develop your teaching skills and coach 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 five years, with an intermediate evaluation (go/no-go) after nine months. You will spend 25% 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. €2,901 max. €3,707).
• 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 this video.

Information

Do you recognize yourself in this profile and would you like to know more?  Please contact
the hiring manager Thiago D. Simão, Assistant Prof, t.simao@tue.nl.

Visit our website for more information about the application process or the conditions of employment. You can also contact 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:

• Cover letter in which you describe your motivation and qualifications for the position.
• Curriculum vitae, including a list of your publications and the contact information of two references.
• Proposal describing the first problem you will tackle and the approach we will use (max 2 pages).
• Links to your MSc thesis and examples of code.

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.