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Field
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objective of the thesis is to model the intermolecular interactions between metabolites and a chemically modified gold surface in the presence of different ions. Molecular modeling will be performed with
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Max Planck Institute of Molecular Physiology, Dortmund | Dortmund, Nordrhein Westfalen | Germany | about 1 month ago
biology to cutting-edge computational modelling—our interdisciplinary team of molecular biologists, chemists and physicists explores the spatial and temporal dynamics of biochemical networks within
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Max Planck Institute for Multidisciplinary Sciences | Gottingen, Niedersachsen | Germany | about 17 hours ago
spectroscopy in combination with photo-bleaching for the determination of the stoichiometry of the complexes and molecular dynamics. The protocols to prepare physiologically relevant particles will be
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application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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microscopy) Flow cytometry Mammalian cell culture (cell models, including iPSC-derived cell lines) Lysosomal immunoprecipitation for multi-omics analysis Chemical synthesis Integration of biochemical, cellular
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PhD Studentship: Preclinical modelling and therapeutic targeting of glioblastoma infiltrative margin
PhD Studentship Advert Title: Preclinical modelling and therapeutic targeting of glioblastoma infiltrative margin Supervisors: Prof Ruman Rahman, Dr Stuart Smith, Dr Phoebe McCrorie Project Overview
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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, with strong training across genome engineering, chromatin biology, and gene regulation in diverse model systems. Extensive experience in CRISPR-based genome editing, mutant line generation, and molecular
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clinically. We will develop cancer biomarkers through statistical models, including AI driven strategies, to predict highly aggressive tissue molecular signatures for mapping future GBM relapse, linking