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. coli, Salmonella, Listeria monocytogenes, Campylobacter). Analysis is typically complicated by the complex nature of food matrices and the frequent need to detect very low numbers of targeted pathogens
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Administration (NASA), and other sources. Job Summary Prospective postdoctoral fellows interested in decision-making in the context of complex natural hazards and environmental change are encouraged to apply for a
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of Neurology; plans, designs, and executes experiments of considerable scope and complexity in the assigned research laboratory; collects and analyzes data for research sponsored by appropriate agencies and
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recognition events to colonization strategies. Within this framework, the advertised postdoctoral project is specifically focused on complex data analyses of plants for improved symbiotic associations with soil
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, Stem Cell Biology, Biotechnology, Biochemistry, or a closely related discipline. Candidates with experience in bioinformatics and omics data analysis are encouraged to apply. Required Related Experience
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. The position will provide training and mentorship in life-course epidemiology, pregnancy and perinatal epidemiology, and the analysis of high-dimensional molecular data. This is a 12-month full-funded position
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expertise in inorganic and organometallic chemistry since heterometallic complexes are targeted. Polymerization catalysis kinetics will be investigated using specialist reactors, in situ spectroscopy
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), and Julio Saez-Rodriguez (Systems Biomedicine, Institute of Computational Biomedicine. If you are a curiosity-driven researcher who enjoys interdisciplinary teamwork and tackling complex biological
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experiments of considerable scope and complexity in the assigned research lab; collects and analyzes data for research sponsored by appropriate agencies and Institutions; identifies and selects problems to be
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Post-Doctoral Associate in the Center for Interdisciplinary Data Science and Artificial Intelligence
of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis Automated theorem proving and formal methods