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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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metaproteomics approaches Analyzing large-scale multi-omics and clinical datasets to investigate individual metabolic responses to diet. The work includes applying advanced statistical and machine learning methods
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | about 2 months ago
-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Open Postdoc
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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle
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of knowledge in the subject of Robotics to develop research in the field, e.g., robot design, control and mechatronics; 4. Publication record in robotics and machine learning, e.g., ICRA, IROS, RSS, CoRL, T
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 11 days ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position in Machine Learning for Single-Cell Genomics (f
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predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time
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of Vienna). About the position: Lead the research group focusing on hybrid quantum algorithms, quantum neuromorphic computing, and quantum machine learning Build your own team (PhD students, postdocs) 4-year
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grasslands and evaluation of land-use intensity, Expertise in classification with machine-learning methods, statistics, spatial analysis and land-use modeling, Experience and interest in conducting fieldwork