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, CSF) and/or advanced workflows such as spatial proteomics is highly desirable Strong collaborative spirit and working in interdisciplinary environments Excellent written and verbal communication skills
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-university research institutes in Germany. PRIF is headquartered in Frankfurt and has a branch office in Berlin. More than 100 employees from research, administration and science communication contribute
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experts from companies and policy makers, as well as communicating findings in policy-relevant time frames and formats. This position is suitable for furthering scientific training according to Section 2
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communication skills What we can offer you: an inspiring and collaborative environment where you can fully realize your passion for education and research, autonomy supportive research environment and diverse
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Researcher / Postdoc for molecular investigations on microbial ecology in deep-sea polymetallic n...
Ecology and Technology group is carrying out work on the impact of manganese nodule mining on deep-sea benthic communities and their functions. The Research focuses on industrial tests of the manganese
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(including the doctoral dissertation) Strong methodological training in quantitative survey and experimental research (Additional asset: experience with using large language models in surveys) Proficiency in
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, B., Holtkamp, E., et al. Integration of variant annotations using deep set networks boosts rare variant association testing. Nature Genetics (2024) Marconato, L. , Palla, G. , Yamauchi, K. A
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genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
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through soft, disordered materials, including auto-regulated networks, composite soft solids, and exotic photonic biomaterials. The lab has two fully funded PhD and/or postdoctoral positions available
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The Network Analysis and Modelling group investigates how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. Using machine learning and network