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thesis on a topic relevant to this project. Proven experience in molecular dynamics simulations of proteins or protein-ligand complexes is an advantage.You possess:- A successfully completed MSc degree in
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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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, your application should include (PDF format): A letter of motivation (max. 1 page) A detailed curriculum vitae. Please include an overview of your experience with molecular dynamics, density-functional
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) to simulate the dynamics of discrete cells and Newtonian and non-Newtonian fluid-structure interaction models to assess how the intracochlear fluid (perilymph) influences RWM deformation. We will also develop
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, or dynamic models to predict gene regulatory interactions. Work with digital twin technology, simulating patient-specific disease progression and treatment responses. Collaborate in an interdisciplinary
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experience with in vivo studies (artikel 9, proefdierkunde), flow cytometry, single cell technology (working in R), microscopical techniques and molecular biology is an advantage With proficiency in English
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thesis on a topic relevant to this project. Proven experience in molecular dynamics simulations of proteins or protein-ligand complexes is an advantage. You possess: A successfully completed MSc degree in
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relevant to this project. Proven experience in molecular dynamics simulations of proteins or protein-ligand complexes is an advantage. You possess: A successfully completed MSc degree in computer science
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in the Molecular Biosensing group (MBx, see www.tue.nl/mbx ) are unique in the world. The sensors are based on reversible single-molecule interactions, for the continuous monitoring of biomolecules
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modelling and atomic scale molecular dynamics and quantum chemical modelling. In doing so, we cover both ends of the lengthscales that are relevant to perovskite solar cells: Effects that cannot be captured