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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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challenge. This project aims to explore data-driven Artificial Intelligence/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines
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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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, including fitting and manipulation of large array-type data sets (using Python, Matlab or equivalent) Ability to communicate well, and work within a collaborative team environment Preferred Knowledge, Skills
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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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. 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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interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
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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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will work on multiple projects funded by NIH/NHGRI. The objective of the position is to develop novel statistical methods and computer software and analyze large scale biological data from biobanks
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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