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. Experience with machine learning techniques for neural data analysis. Track record of publications in high-impact journals and successful grant applications. Work Environment: This position is part of a
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, statistics). Excellent organizational skills and attention to detail in experimental design and data tracking. Working knowledge of machine learning techniques for high-throughput data interpretation
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crystal handling, SPR machines, and two libraries of fragments (small molecules <300 Da) tailored for SPR and X-ray crystallography. This setup enables a full workflow for fragment-based drug discovery
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used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
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include data science management and development of novel and executing existing computational methods including machine learning and deep learning methods to integrate genomics, transcriptomics and
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piglets who are unable to acquire own mothers’ colostrum. The majority of the experimental in vivo work is located at Frederiksberg Campus, albeit but with some investigations under commercial farming
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: www.jura.ku.dk . The Faculty actively supports efforts to learn Danish. Qualification requirements Employment as a Postdoc requires academic qualifications at PhD level. More information on careers at UCPH and the
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programmers. You will also work closely together with course teams to develop data generation, data analysis, modeling, simulation, and machine learning workflows as well as develop custom data science-related