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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
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to advancing machine learning in biomedicine. The Program focuses on developing and applying cutting-edge AI approaches to address key challenges in molecular biology, clinical research, and translational
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, storage, accessibility/sharing, archiving, publication, and preparing data for machine learning applications. The Research Training Group RTG 3120 offers, subject to the availability of resources, a
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of equivalence with a German qualification. Skills and experience Extensive research experience in the field of artificial intelligence, machine learning, and deep learning with a focus on language
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machine learning approaches to quantitatively analyze experimental data and predict emergent multicellular behaviors under varying mechanical and chemical environments. For more information about our lab
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, integrative biology approach that utilizes human pluripotent stem cell based model systems, high throughput functional genomic screening and big data based machine learning, bridging the scales from genetics
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machines into the cellular context in space and time, how stress factors influence these processes, and how the cellular network enables their robust functioning. Research Focus 3 Microbes providing
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Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and selectivity mechanisms in
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Senior Scientist / Group Leader on Bioinformatics / Computational Biology on RNA Regulation in Disea
, and validate computational findings Apply machine learning and statistical modeling techniques to identify patterns and predict functional impacts of RNA modifications Contribute to publications
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PhD Student (gn*) Job Id: 11029 Limited to 3 years | Part-Time with 65% | Salary according to TV-L E13 | Institute of Molecular Tumor Biology We are UKM. We have a clear social mission and, with