158 computational-physics-"https:"-"https:"-"https:"-"IFM" Postdoctoral positions at Nature Careers
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at the Department of Electrical and Computer Engineering, Aarhus University, where we are advancing communication-efficient and distributed foundation model inference across the computing continuum
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Postdoctoral Research Associate - Hybrid Computational-Experimental Scientist in Bacterial Drug Resp
in mentoring and shaping the lab's interdisciplinary culture. We Are Looking For Someone Who • Has a PhD in computational biology, microbiology, systems biology, engineering, physics, CS, or a related
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application instructions), please visit: https://www.mpg.de/en/max-planck-postdoc-program . To submit your application online, please visit: https://postdocprogram.mpg.de The application deadline is April 13
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international collaboration partners Support and administer internal web and Linux servers Your Profile Academic degree (master's and Ph.D.) with a background in computer science, bioinformatics, physics
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the interface of computational biology, molecular science and translational medicine, generating large multi-omic datasets that require robust, reproducible analysis to identify rare signals with high accuracy
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. The candidate will lead computational analyses of these datasets, using the laboratory’s suite of existing AI/ML tools to assign structures to unidentified peaks in metabolomic datasets (e.g., https
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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various disciplines: computer scientists, mathematicians, biologists, chemists, engineers, physicists and clinicians from more than 50 countries currently work at the LCSB. We excel because we are truly
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Job Description Collaborates with new and existing program partners to support research initiatives, including the collection, analysis, and interpretation of primary and secondary data to address
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, providing direct feedback on theory analysis and further predictions. The goal is to develop a theoretical and computational approach that has strong predictive power for finding completely new types