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Researcher to join the Machine Learning in Biomedicine group, in collaboration with the Precision Cancer Epigenomics group at NCMM, through the NORPOD program. Summary of the project Human tumors
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candidate to have a PhD degree from a relevant field with skills and experience in image analysis and machine learning. Familiarity with the volumetric microscopy image data and statistical methods
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to develop solution algorithms for these problems that are based on machine learning. The project will study inverse problems for linear and non-linear hyperbolic and elliptic PDEs by applying analysis
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and associate the findings to clinical data using machine learning. The postdoctoral fellow will perform studies on the metabolism of healthy intestinal cells and tumour initiating cells using state
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-scale computational approaches (molecular dynamics simulations, quantum chemistry, machine learning, etc) are applied to study the mechanistic aspects of biomolecules in great depth. The work is done in
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(Helsinki Institute of Life Science, University of Helsinki) is looking for a postdoctoral researcher with background in neural network models . Our group develops computational models, machine learning and