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members, and contribute to collaborative projects. Essential requirements: PhD in stem cell biology, haematology, molecular biology, or related disciplines. Extensive experience in hematopoietic stem
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and supporting other group members whenever needed; Sharing and discussing research results with collaborators. Mandatory requirements: PhD in immunology, cell biology or equivalent (or PhD is going
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biological systems, also in collaboration with other researchers and companies. Your profile Applicants should hold a PhD in Computer Science, Computer Engineering, Artificial Intelligence, Physics
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of climate model output by means of classical statistical and machine-learning methods #coordination of scientific workflows among project partners Your profile #Master's degree and PhD degree in meteorology
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, probabilistic models Representation learning, self-supervised learning, foundation models Data analysis, non-linear statistics, knowledge management Your profile PhD in Computer Science, Bioinformatics
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scaling and generalization behavior Roll out the model to the global user community Requirements PhD or MSc in computer science, physics, mathematics or a related discipline Experience with large-scale HPC
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should have a strong background in a quantitative discipline and an interest in neurodegenerative diseases. Essential: You obtained a PhD in Computational Neuroscience, Bioinformatics, Computer Science
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enjoys scientific discussion and interdisciplinary science. To be considered for this position, you must have a PhD in a field like physics and applied mathematics or a field related to one
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Postdoctoral Researcher as a Junior Research Group Leader (m/f/d) - Research on and Implementation o
newly created PhD position" (75% E13 TV-L). The team will also include a technical staff member responsible for maintaining the TüDiLab and assisting with empirical studies - A modern and well-equipped
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contribute to development of research grant applications. Your profile The applicants should hold a PhD in structural dynamics with focus on data-driven methods (e.g., for input/state/parameter estimation) and