PhD Position in Statistical Physics and Probability Theory
3 weeks ago
The PhD position in the Mathematical Foundations of Bias in ML is an exciting opportunity for a candidate to explore the bias generation and amplification process in machine learning. The successful candidate will learn and develop sophisticated theoretical methods from statistical physics and probability theory, applying them to relevant societal problems. In this role, you will be part of a dynamic, international environment, collaborating with leading experts in the field. The PhD program is a joint effort between Chalmers University of Technology and the University of Gothenburg, offering a unique chance to work on cutting-edge research.
- Develop and apply theoretical methods from statistical physics and probability theory to understand bias generation and amplification in ML.
- Collaborate with leading experts in the field, contributing to the advancement of ML research.
- Work in a dynamic, international environment, gaining valuable experience and knowledge.
As a PhD student, you will be enrolled in a graduate program in the Department of Computer Science and Engineering. The position includes 20% departmental work, primarily as a teaching assistant for Chalmers' undergraduate and master's-level courses or performing other departmental duties. This opportunity will equip you with the skills and knowledge necessary to make significant contributions to academia and the broader research community.
Research within the department spans a wide spectrum, from theoretical foundations to applied systems development. The DSAI division, one of the four divisions, focuses on both fundamental and applied research in AI and machine learning, upholding high international standards. The department is organized into four divisions and employs approximately 270 people from over 30 countries. High-quality education is provided at the bachelor's, master's, and graduate levels, with over 120 courses offered each year.
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Expert Researcher in Bias Mitigation for AI
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PhD Researcher in Machine Learning Bias
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