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Field
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collaborative Postdoctoral Fellow to join our team focused on understanding cancer biology and metabolic vulnerabilities in lung cancer. We are particularly interested in candidates with strong molecular biology
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interdisciplinary structural biologists is expanding. We are looking for a Research Fellow fascinated by the structural basis of molecular functions. You will study the structure-function relationships in RNA-protein
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interdisciplinary structural biologists is expanding. We are looking for a Research Fellow fascinated by the structural basis of molecular functions. You will study the structure-function relationships in RNA-protein
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in basic molecular biology skills. · Experience in animal models. · Experience in immunofluorescence staining and flow cytometry. · Good written and verbal communication skills
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in studying the molecular, cellular, and metabolic mechanisms leading to obesity, diabetes, and cancer. Expertise in using mouse models to study metabolic diseases is preferred. For a complete list of
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systematic perturbation approaches. Systems Biology: Integrate multi-omic datasets to map the molecular networks influenced by mito-MPs. Machine Learning: Apply cutting-edge protein language models and AI
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Details Title Molecular & Integrative Physiological Sciences Postdoctoral Fellowships School Harvard T.H. Chan School of Public Health Department/Area MIPS/Environmental Health Position Description
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models, and animal models of cardiomyopathy, heart failure and vascular disease. During past years, the lab has published in Nature Cell Biology, Developmental Cell, Development, Genome Biology, Nature
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Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning approaches
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Qualifications: PhD in immunology, cancer immunology, autoimmune diseases, human genetics, molecular biology or biochemistry Experience in autoimmune diseases, preclinical animal disease models, multi-color flow