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Research Fellow to join a new interdisciplinary group studying cancer evolution, metastasis, and therapy resistance using molecular recorders – tools that enable cells to log aspects of their own biology
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the molecular mechanisms driving therapy resistance in human cancers. The research project focuses on understanding the molecular mechanisms by which MAPK4 and/or COP1 regulate cancer progression and therapy
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Background. The tumor microenvironment (TME) is a highly heterogeneous and dynamic ecosystem that significantly influences cancer progression, metastasis, and therapeutic response. Traditional bulk
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of projects in the lab or assisting PI/postdoc with the projects, so prior research experience is necessary. In particular experience in the areas of molecular and cell biology will be favored
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A postdoc position in the Torben Heick Jensen lab, Aarhus University, Denmark: Mammalian Nuclear ...
A postdoc position is available in the laboratory of Torben Heick Jensen at the Department of Molecular Biology and Genetics, Aarhus University, Denmark. Expected start date and duration of
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of Excellence for Leukemia Studies with access to cutting-edge technology and resources. The successful candidate will ideally have a PhD (or will obtain a PhD) with a focus on molecular biology, cancer
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will involve a combination of simulation and statistical modelling. Your key responsibilities will be: Lead analysis of State response data to estimate detection, occupancy, and spread of PSHB Engage
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, aiming to improve diagnostics and clinical risk stratification through molecular profiling of affected patients. Description of the project Our research team explores the molecular underpinnings
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of molecular reactions occurring at the surface of various materials. In addition, computational fluid dynamics (CFD) simulations combined with microkinetic modeling will be carried out to study the heat
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Department of Biomedical Informatics is a highly dynamic and multidisciplinary environment that has strengths in bioinformatics, global health informatics, imaging informatics, machine learning, mHealth