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analyse complex data from emerging genomic pathology approaches, including CRISPR, single cell sequencing, spatial transcriptomics, and image analysis to address biologically- and clinically-driven
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of mutational processes in human health and disease. We are an interdisciplinary team of experimental, computational, and clinician scientists allowing us to generate and analyse complex data from emerging
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Postdoctoral Associate in Computational Neuroscience at Yale The Post-Doctoral Associate will develop predictive, gene-regulatory networks linked to Parkinson’s and other neurological diseases in
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-on experience in blockchain technology (preferably Ethereum) and/or machine learning. Solid foundation in computer network and/or data analysis. Strong programming skills, preferably in Java. Ability to work
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development reviews, leadership and entrepreneurship training, collaborative training opportunities, and networking and conferences. Qualifications: PhD in Molecular Biology, RNA Biology, Biophysics, or a
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a robust academic and professional network, preparing for leadership roles in academia, policy, or industry. Receive the IT support required by their research (e.g. specialized software or computation
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independence, long-term career advancement, and the development of an intramural and extramural academic network tailored to the candidate’s interests. This fellowship will allow candidates to develop, or expand
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in candidates with interest in algorithms, blockchains and cryptocurrency, causal inference, game theory, learning, machine learning, market design, and networks, but all subjects at the intersection
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pressures. · Analytical Skills: Ability to conceptualize and conduct complex analyses that involve different typs of data (clinical, genetic, neuroimaging) · Capacity for independent work
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insights into activation, complex formation, signaling, and ligand recognition of understudied membrane receptors involved in recognition of sterol signaling molecules. To this end we apply a