Summary
The Hasso Plattner Institute (HPI) is inviting applications for a PhD candidate position aimed at developing efficient reasoning architectures in the domain of medical AI. This position is set to strengthen research in AI, focusing on creating compact, private, and auditable medical applications to address critical health decisions.
PhD Candidate in Efficient Reasoning Architectures for Medical AI, Hasso Plattner Institute, Potsdam-Babelsberg, Germany
Designation
PhD Candidate (f/m/x)
Research Area
- Efficient Reasoning Architectures
- Medical AI
- Deep Learning
- Data Attribution
Location
Hasso Plattner Institute, Potsdam-Babelsberg, Germany
Eligibility/Qualification
| Qualification Criteria |
|---|
| Master’s degree (or equivalent) in computer science, machine learning, mathematics, or closely related field |
| Strong background in transformer architectures, efficient deep learning, recurrent or state-space models, or neural architecture design |
| Solid foundations in optimization, learning theory, or computational complexity |
| Proficiency in Python and modern deep learning frameworks (PyTorch preferred) |
| Strong publication record or demonstrated research potential |
| Interest in health and medical AI applications is a plus but not required |
| Fluent in English; German is welcome but not required |
Job Description
- Design and investigate parameter-efficient transformer architectures for high effective model depth with minimal parameter cost.
- Develop adaptive compute allocation and early-exit mechanisms for efficient deployment on resource-constrained devices.
- Establish and evaluate compact model baselines (sub-4B parameters) on medical reasoning benchmarks.
- Investigate learning-theoretic foundations connecting looping, reasoning, and algorithmic reasoning in compact architectures.
- Contribute to open-source evaluation toolkits and benchmarks for efficient medical AI.
- Engage in publication efforts at top-tier venues and contribute to collaborations within the research group.
How to Apply
Interested candidates should submit their applications through the HPI career page, including:
- Motivation letter
- CV
- Relevant transcripts or degree certificates
- Sample of scientific work (e.g., thesis, excerpt, or publication)
- Reference letters (if available)
- Salary requirements
Last Date for Application
May 31, 2026
This scholarship represents an exceptional opportunity to contribute to impactful research at the intersection of AI, health, and privacy with renowned international partners.
