13 machine-learning-phd-in-denmark Postdoctoral positions at Heidelberg University in Germany
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hosts. The project is centered on the integration and analysis of multiomics datasets utilizing advanced machine learning approaches and biological network analysis. The successful candidate will join an
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Limitation:Temporary (2 years) Contract:TV-L Your tasks Develop and implement computational pipelines for processing and analyzing ONT RNA/cDNA sequencing data. Apply machine learning and signal processing approaches
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approaches and will integrate novel hardware (including electrode arrays, microdevices, analytical systems) into automated robotic pipelines You will also apply machine learning-based analyses to imaging and
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the United Kingdom, USA, Denmark, and Germany. In addition to this core project, the research group works on a wide variety of research, with foci being medication effectiveness, health services research, and
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in the consortium. Your profile PhD in the field of mass spectrometry-based proteomics Ample experience in mass spectrometry-based proteomics, including sample preparation and hands-on use of modern
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Cancer). Your profile PhD in Bioinformatics, Computational Biology, Data Science, or related field. Experience in multi-omics data analysis and/or drug screen data processing. Experience with HPC/cloud
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circulation Your Profile PhD in a relevant field (or close to completion) Solid experience working with Drosophila Prior experience in lipid metabolism research is a plus, but not required Strong communication
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students and technicians Maintain accurate documentation of protocols and instrument logs; liaise with service and facility management Your profile: PhD (or equivalent) in analytical/biological chemistry
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-scale controllable, and cost-efficient disease models by bringing together experts in physical chemistry, physics, bioengineering, molecular systems engineering, machine learning, biomedicine, and disease
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applicant will have good communication and organisational skills and a PhD in a relevant area (or be in the final stages of completion). Candidates are expected to be highly motivated and to work