Postdoctoral Research Associate | Akademische* Mitarbeiter*in (m/w/d)
Hochschule für Technik, Wirtschaft u. Medien Offenburg
Job Summary
This full-time PostDoc position at the Institute for Machine Learning and Analytics (IMLA) within Offenburg University of Applied Sciences focuses on the 'Lab2Device' project. The successful candidate will lead research in multi-objective model compression and neural architecture search (NAS). Day-to-day responsibilities include conducting independent literature reviews, evaluating existing methodologies, and designing innovative algorithmic approaches. A significant portion of the role involves publishing scientific papers at top-tier AI conferences, co-supervising two PhD students, and developing prototypes in collaboration with industrial partners. Additionally, the role includes teaching responsibilities. This position is ideal for an ambitious researcher looking to bridge the gap between high-level machine learning theory and practical embedded hardware applications. The role offers a 3.5-year contract, flexible working hours, and access to corporate benefits within a highly innovative and internationally oriented academic environment in Baden-Württemberg.
Required Skills
Education
Completed university degree (Master's or equivalent) in Computer Science, Electrical Engineering, or a related field; plus a relevant PhD in Neural Architecture Search, AutoML, Model Compression, Multi-objective Optimization, or Embedded Hardware.
Experience
- Professional experience in conducting independent scientific research and literature reviews
- Proven track record of publications in top-tier Machine Learning or AI conferences and journals
- Extensive experience with modern ML/AI frameworks such as PyTorch or JAX
- Experience in the design and implementation of algorithmic approaches
- Experience in co-supervising doctoral students or junior researchers
- Experience in industrial prototype development and collaboration
Languages
Additional
- The position is limited to a duration of 3.5 years. Candidates with foreign degrees must provide proof of equivalence to a German degree. Applications must be submitted exclusively via the online application tool by April 13, 2026.
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