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to join a collaborative, diverse, and creative research team. Experience in molecular biology, data analysis, and animal experiments is an advantage. The successful candidate will apply molecular and
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fellow, you will be empowered to own a project end-to-end, from model design and assay development to data generation, analysis, and publication. You will be immersed in a scientifically rich and
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the Human Pancreas Analysis Program (HPAP) and related consortia, providing access to deeply phenotyped T1D samples, islet organoids, and rich multi-omic datasets. Key Responsibilities Design and
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the department and across the university and join a cross-institutional research team focused on neuroscience, aging, and -omics data analysis. Responsibilities Develop and apply innovative machine learning
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, troubleshooting results, data analysis, writing manuscripts, contributing to grants, and presenting their work at national and international conferences. Specific skillsets include tissue culture, flow cytometry
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cloning, PCR, flow cytometry, and analysis of immunohistochemistry, as well as other standard wet-lab assays. Candidates will also be responsible for analyzing genomic and transcriptomic datasets with
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and a proficient understanding of next generation sequencing, analysis, and bioinformatics), (3) project management and scientific writing experience, and (4) excellent communication skills and a
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experience is beneficial Experience with the analysis and interpretation of large data sets, in particular high-throughput sequencing data from eukaryotic organisms Solid skills in programming and scripting
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to prevent the onset of cancer. In parallel, our research is dedicated to advancing our understanding of bladder tumor evolution biology through the analysis of next-generation sequencing (NGS) data and the
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desirable. Basic computational analysis skills (e.g., R or Python for sequencing data) are a plus but not required. Candidates must be team-oriented, organized, and enthusiastic about collaborative science