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hosts. The project is centered on the integration and analysis of multiomics datasets utilizing advanced machine learning approaches and biological network analysis. The successful candidate will join an
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funded German research initiative. Project Description: Carbon black is an indispensable component of numerous everyday products – from car tires and seals to paints and plastics. However, its production
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, prototyping, programming (device communication, databases) Experience in the following areas is also a bonus: electrocatalysis, rheology, coating technology, machine learning Intrinsic motivation to show
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very latest issues that impact our society
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and machine learning methods. Knowledge of constraint-based metabolic modelling will be considered a strong advantage. The ideal candidate is highly motivated, capable of working both independently and
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research experience, preferably in programming languages, compilers, applied mathematics, and optimization techniques a strong background in compiler, code generation, and machine learning would be
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robotic system design, humanoid robot development, manipulation and bimanual manipulation, control, or machine learning for robotics. Excellent project management skills to meet and achieve the expected
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in medicine and other study programmes and graduate initiatives in which the Faculty of Medicine is involved is expected. Beyond the core research area, the appointee will also teach in all degree
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies