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modelling of materials and machine learning. Experience in atomistic modelling (molecular dynamics, density functional theory) and machine learning is important, as well as a strong interest in pursuing
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the consistent further development of its profile-forming priority research areas Molecular Cell Biology, Neurosciences, Cardiovascular Medicine and Oncology. With its German Centers for Health Research partner
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protocols and generation of data, we can offer a challenging job in a dynamic research environment. The successful applicant will be placed in the research unit Ruminant Nutrition: https://anivet.au.dk/en
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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Rasmus Siersbæk at the Functional Genomics & Metabolism Research Unit at Department of Biochemistry and Molecular Biology, University of Southern Denmark. There is an opportunity for an introductory
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laboratories and Institute are well equipped in methods for nanomedicine preparation and characterization, cell culture and methods in molecular and cell biology to characterize, and quantify nanomedicine
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We are looking for a motivated and dynamic research assistant to join Dr Dan Ma’s lab at Aston Medical School on a two-year Academy of Medical Sciences-funded project focused on neurodegeneration
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high-quality scientific publications and actively seeking external funding to support and expand research activities. Your profile You should hold a PhD in medical sciences, biology, molecular biology
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) through molecular and material engineering, as well as device engineering. The research will involve material design, synthesis and characterisation, solar cell assembly, testing and characterisation under