Student Research Assistant (HiWi) @IDEA Lab

The successful applicant will be part of the Image Data Exploration and Analysis (IDEA) lab @AIBE FAU, which is the research group of Prof. Bernhard Kainz. We have pioneered new methodological developments in the field of medical image analysis and machine learning as evidenced by several international awards, prizes, and best paper awards. The group is internationally renowned for its research in medical deep learning, which has been proven by publications at top conferences (MICCAI, CVPR, ECCV) and in prestigious journals (IEEE TMI, Medical Image Analysis, npj Nature Digital Health, The Lancet, etc.).

We are seeking a motivated student research assistant to efficiently train conditioned and unconditioned diffusion models on a novel dataset. The role involves working with deep learning frameworks such as PyTorch, utilising HPC environments for large-scale training, and optimising model performance. Ideal candidates will have experience in deep learning, Python programming, and GPU acceleration, along with strong organisational and teamwork skills. This is an excellent opportunity to gain hands-on experience in generative AI research while contributing to cutting-edge model development.

Notwendige Qualifikationen:

• Familiarity with training deep learning models, preferably diffusion models
• Experience with High-Performance Computing (HPC) environments at FAU/NHR
• Highly motivated and proactive in tackling technical challenges
• Strong coding skills in Python and PyTorch, with experience in writing efficient and well-structured code
• Good organisational skills and attention to detail, especially in managing experiments and datasets
• Ability to manage time effectively and work under deadlines

Befristetes Forschungsvorhaben

Please send your cover letter, curriculum vitae, transcript of records and a ~100-word motivation letter with the following subject line: DIF2025. Applications with missing information will be considered incomplete and will not be processed. We are looking for a potential student assistant who targets an employment for one semester (April-October), the ideal candidate would be in 2./3. master semester. Please send your application asap and do not wait until the deadline.

The Department AIBE and FAU see itself as a progressive and forward-thinking employer. We welcome your application regardless of your age, gender, cultural and social background, religion, belief, disability or sexual identity. Friedrich Alexander University promotes professional equality for minority groups and women. These groups are therefore expressly encouraged to apply. Severely disabled persons within the meaning of the Severely Disabled Persons Act will be given preferential consideration in the case of equal professional qualifications and personal suitability if the advertised position is suitable for severely disabled persons. At the applicant's request, the Equal Opportunity Officer may be called in for the interview without any disadvantage to the applicant.