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background in statistics, and familiarity with large data sets such as metabolomics or epigenetic sequencing. Experience in epigenetics or gene regulation is a plus. Experience with statistical analysis tools
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team. · Applies statistical methods to large-scale, longitudinal training-related behavioral data. · Maintains substantial knowledge of state-of-the-art principles and theories
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. You will have demonstrable experience in the analysis of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single
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in data integration, model design, and large-scale training by combining multi-modal scientific data, knowledge graphs, physics-aware machine learning, and GPU/HPC computing to develop transparent and
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assays such as light/dark, von Frey, and facial grimace. Additionally, the successful candidate must possess technical proficiency in MATLAB and Python for data analysis and processing Duties to include
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 17 days ago
data analysis methods to study biological memory circuits and their applications to machine learning. Building on recent work from the Fiete Lab, the role focuses on identifying principles of biological
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Science at Fred Hutch Recent advancements in statistics, computational techniques, and experimental technologies are transforming how we generate and analyze data. This big data has big potential
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data collection activities, ability and interest in working with large datasets, and interest in working with interdisciplinary teams of researchers. The expectation is that the scholar would help lead
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. Proficiency in SQL, Python/R, or similar tools; experience with big data platforms , machine learning, and data warehousing. Commitment to quality, integrity, confidentiality and compliance. Excellent
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biology and genomics. We are collaborative and multidisciplinary, combining organic chemistry, cell and molecular biology, protein biochemistry, and large-scale genetic screening in our research approach