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, or a closely related discipline with a strong academic record Genuine interest in data-driven and physics-based modeling, molecular simulations, and their application to bioprocesses and bioseparations
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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for epidemiology that can be applied at the population level and also at the molecular and cellular level for biological applications. Qualifications ● Graduated with an MS degree in Computer Science, Mathematics
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About the role As the Research Assistant within the Division of Cardiovascular Medicine, you will explore the molecular mechanisms of atrial fibrillation and cardiac fibrosis in humans and
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validated on a wastewater recycling pilot plant. Suitable methods for process analysis and characterization will be extended and the chemical-physical relationships will be studied using molecular and
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HepSYS (Functional genomics of viral hepatitis and liver disease), which cover all areas of molecular and cellular biology at the levels of molecular factors, genes, cells and organisms from model systems
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research outcomes will set you apart. A degree in Chemistry, Biochemistry, Pharmacology, or a related field (or equivalent experience). Demonstrated experience in molecular modelling, simulations, and
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infection. Minimum of 1 years of research experience in immunology or animal models of viral infection, including experience gained during doctoral studies. Proficiency in laboratory techniques such as flow
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Research Assistant Professor, Research Associate Professor, Assistant Professor, Associate Professor
and molecular bases of chronic health conditions and/or human disease. A variety of experimental approaches, encompassing in vivo, in vitro, and in silico models, will be considered. Candidates