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data using multivariate statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft
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statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft matter and nanomaterials
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mentor; and publication of research findings/scholarship during postdoc appointment period. Projects in the CEL group include comparative phylogenomic analysis of invertebrates, including Hawaiian insects
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 8 days ago
for data-intensive digital systems research. The Department of Machine Learning for Infection and Disease is looking for a Postdoc (f/m/d) on Generative AI for de Novo Protein Design. Your tasks # Design of
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team in the AI in Medicine Lab (www.aimlab.ca ). This position is based in the School of Biomedical Engineering. The successful candidate will work in the AI in Medicine Lab, applying machine learning
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, as well as quantum simulation, quantum computing, and machine learning. Currently, ECT* hosts 5 permanent researchers, 4 postdoctoral associates, the ECT* Director, 3 Ph.D. students, and 4
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relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have documented experience in
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development of analytical solutions, data analysis and machine learning. Candidates should have a demonstrated record of scientific publications in international journals and participation in conferences
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 8 days ago
PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis or machine learning, proficiency in deep learning techniques (CNN, VIT
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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome