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Field
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experience in life cycle assessment (LCA) and related tools for managing large data sets to evaluate natural resources needed to advance emerging technologies. The candidate will lead their primary project and
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experience in Oxford Nanopore Technologies (ONT) sequencing and bioinformatics A track record of research in microbiome science, metagenomics, whole genome sequencing, big data analysis, machine learning, and
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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computational biology/chemistry, machine-learning for biological or chemical data, and drug discovery/design. Mentorship is taken seriously and every effort will be made to ensure the candidate is able to achieve
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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] Subject Areas: Computational Biology / Data Analytics Machine Learning / Machine Learning Analytical Chemistry / Current Advances in Chemistry & Biochemistry Computational Science and Engineering
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. Contribute to the development of research grants for funding of lab training and research. MINIMUM QUALIFICATIONS PhD in neuroscience, neurobiology, machine learning, biomedical engineering, or related field
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. Ready to be part of our team? Let’s shape the future together! About the team: The Computational Materials Discovery group is looking for a postdoctoral researcher working in the field of machine learning
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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following position Postdoctoral researcher (m/f/d) in Environmental Data Science and Machine Learning for the project BoTiKI Location: Görlitz Employment scope: full-time (40 weekly working hours) / part