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-of-computing-science/ Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data driven models for complex data, including temporal data
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for physical AI and physics‑based simulation for complex mechanical systems. We are now seeking a postdoctoral researcher for a project aiming at physics‑informed autonomous control of machines operating in
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will also use focussed ion beam milling scanning electron microscopy (FIB-SEM) to prepare infected cells for in situ cryo-ET. The resulting tomographic data will be analysed by machine-learning assisted
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loop/TAD structures. - Perform comparative analyses versus Populus tremula; apply network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce
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completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service
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, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant
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be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service, or similar circumstances, as well as clinical practice
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interpretation of culture and memory, as well as its influence on creativity and the dynamics of human-machine interaction. Second, it investigates how collaborations driven by AI are reshaping creative
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This position is intended as a career-development opportunity for early-career researchers. Priority will be given to candidates who completed their PhD within the past three years. Exceptions may be granted in
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manuscript preparation and the supervision of students. Eligibility The candidate shall have a PhD, or a foreign qualification deemed to be the equivalent of a doctorate in biology, genetics, biochemistry or a