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Postdoc (f/m/d): Machine Learning for Materials Modeling / Completed university studies (PhD) in ...
Area of research: Scientific / postdoctoral posts Starting date: 01.07.2025 Job description: Postdoc (f/m/d): Machine Learning for Materials Modeling With cutting-edge research in the fields
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances, as well as clinical practice
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bioinformatics, with a particular emphasis on performing analysis of high-dimensional data, which can be sequencing and/or imaging-based. Experience working with AI and machine learning approaches are considered a
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Director of the GIBH Center for Cell Lineage Atlas,with research expertise in cell lineage dynamics. Deputy Director of the GIBH Center for Biomedical Digital Science, with research expertise in AI/machine
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profile PhD (awarded within the last 5 years) of high quality, ideally in machine learning (in the broad sense), complemented by a strong mathematical foundation in probability and/or statistics Research
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and Fluidigm technologies at UTHSC. Qualifications PhD in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, or a related field. Strong background in machine learning, data
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theory, and machine learning to quantify and understand cancer biology. We are seeking a highly motivated Postdoctoral Researcher to develop new computational methods for the analysis and interpretation
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Postdoc position (f_m_x) ,,Combining Physics-Based Machine Learning and Global Sensitivity Analys...
“Geosystems”), we are looking for a: Reference Number 10337 Are you seeking a PostDoc project at the interface between geoscience, machine learning and mathematics – with an application to the highly relevant