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collaboration with the team. Your profile PhD degree in physics, materials science, chemistry, electrical engineering or a related discipline Knowledge of UHV and thin-film technology Prior experience in PVD and
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antibody discovery Good knowledge of single-cell RNAseq workflows such as 10X genomics or DropSeq, experienced in flow cytometry Good knowledge in cell biology and biochemistry Prior experience in
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profile PhD degree in physics, materials science, chemistry, electrical engineering or a related discipline Knowledge of UHV and thin-film technology Prior experience in PVD and surface science Prior
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expertise and creativity to reduce violence and promote peace in conflict-affected contexts. Thereby, we contribute to more impactful peacebuilding processes, a stronger knowledge-driven environment, and
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to advance knowledge in the following domains: Formal verification and interactive theorem proving (Rocq, Lean) Secure and high-performance computer systems, including ML infrastructure We seek outstanding
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with help from a bioinformatics facility Your profile Hands-on experience in cell biology and NGS Good knowledge in T-cell expansion and therapy Motivated in driving tech development Prior experience in
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experience AI-assisted theorem proving or algorithm discovery is an asset You have working knowledge of numerical analysis, ideally numerical methods for PDEs You are independent and comfortable with open
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of domain-specific data and knowledge. Develop new tabular foundation-model approaches where existing pre-trained models are insufficient, with a particular focus on transferability across heterogeneous
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drive innovations in understanding vision and its diseases and develop new therapies for vision loss. It is a place where your expertise will be valued, your abilities challenged, and your knowledge
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, investigating efficient adaptation strategies and the use of domain-specific data and knowledge. Develop new tabular foundation-model approaches where existing pre-trained models are insufficient, with a