PhD student in AI / Machine Learning - Reinforcement Learning

This PhD position offers a unique opportunity to dive into the exciting area of reinforcement learning within the broader landscape of AI and machine learning. As a candidate, you'll have the chance to develop exciting theoretical concepts and innovative methodologies, all while making tangible contributions to real-world applications with practical impact. Moreover, the PhD student will enjoy working in a diverse, collaborative, supportive and internationally recognized environment with collaborations with a number of internationally leading research groups.

About the position
This position revolves around the fundamental principles of AI and machine learning, with a specific emphasis on reinforcement learning. Machine learning encompasses a range of data-driven techniques that derive models for tasks such as prediction, exploratory data analysis, and explanation. The primary focus of this position is on reinforcement learning which examines the interactions between an agent and its environment, aiming to maximize cumulative rewards (to reach the goal as efficient as possible). Within this project, we will develop novel reinforcement learning methods considering aspects such as sample efficiency, robustness, efficient training and inference, multi-agent reinforcement learning, etc. This position will explore fascinating theories and innovative methods while also giving you the chance to investigate them in interesting real-world applications.

The research group of Morteza Haghir Chehreghani is based in the Division of Data Science & AI (DSAI) in the Department of Computer Science and Engineering (CSE). Our primary focus lies in the development of advanced AI and machine learning methods and their application across various domains. Currently, our research is concentrated on areas such as reinforcement learning, decision making under uncertainty, unsupervised learning, and generative AI.

Information about the division and the department
The CSE department is a joint department at Chalmers University of Technology and the University of Gothenburg, with activities on two campuses in the city of Gothenburg. The department is divided into four divisions, and employs around 270 people from over 30 countries. Research in the department has a wide span, from theoretical foundations to applied systems development. We provide high quality education at the bachelor's, master's, and graduate levels, offering over 120 courses each year. The Data Science & AI (DSAI) division is one of four divisions in department with focus on fundamental and applied research on AI and machine learning at high international standards. Research in our division is collaborative and interdisciplinary with strong connections to various industries (e.g., pharmaceutical, transport and energy sectors).

Major responsibilities
The major responsibilities for a PhD student position in the division include conducting doctoral research within the framework of the outlined research project and coursework. The PhD student will be enrolled in a graduate program in the Department of Computer Science and Engineering.

The PhD student is expected to develop novel ideas and communicate scientific results orally as well as in written form. In addition, the position includes 20% departmental work, mostly as a teaching assistant in Chalmers' undergraduate and masters-level courses or performing other departmental tasks.

Read more about doctoral studies at Chalmers here .

Qualifications
To qualify as a PhD student, you must have a master's level degree corresponding to at least 240 higher education credits in a relevant field.

The position requires sound verbal and written communication skills in English. If Swedish is not your native language, Chalmers offers Swedish courses.

Contract terms
Full-time temporary employment. The position is limited to a maximum of five years.

We offer
Chalmers offers a cultivating and inspiring working environment in the coastal city of Gothenburg .
Read more about working at Chalmers  and our benefits  for employees.

Chalmers aims to actively improve our gender balance. We work broadly with equality projects, for example the GENIE Initiative on gender equality for excellence . Equality and diversity are substantial foundations in all activities at Chalmers.

Application procedure
The application should be marked with reference number 20240146 and written in English. The application should be sent electronically and be attached as PDF-files, as below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.

CV:(Please name the document: CV, Family name, reference number)
• CV
• Other, for example previous employments or leadership qualifications and positions of trust.
• Two references that we can contact.

Personal letter:(Please name the document as: Personal letter, Family name, ref.number)
1-3 pages where you:
• Introduce yourself
• Describe your previous experience of relevance for the position (e.g. education, thesis work and, if applicable, any other research activities)
• Describe your future goals and future research focus

Other documents:
• Copies of bachelor and/or master’s thesis.
• Attested copies and transcripts of completed education, grades and other certificates, e.g. TOEFL test results.

Use the button at the foot of the page to reach the application form. 

Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered.

Application deadline: 2024-06-10

For questions, please contact:
Associate Professor Morteza Haghir Chehreghani, Data Science & AI division, CSE,
[email protected]

*** Chalmers declines to consider all offers of further announcement publishing or other types of support for the recruiting process in connection with this position. ***

Chalmers University of Technology conducts research and education in engineering sciences, architecture, technology-related mathematical sciences, natural and nautical sciences, working in close collaboration with industry and society. The strategy for scientific excellence focuses on our six Areas of Advance; Energy, Health Engineering, Information and Communication Technology, Materials Science, Production and Transport. The aim is to make an active contribution to a sustainable future using the basic sciences as a foundation and innovation and entrepreneurship as the central driving forces. Chalmers has around 11,000 students and 3,000 employees. New knowledge and improved technology have characterised Chalmers since its foundation in 1829, completely in accordance with the will of William Chalmers and his motto: Avancez!
 

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