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, fluorescence lifetime and vibrational imaging methods. Large-scale and high-throughput imaging and analysis pipelines: data acquisition and analysis to characterize cell-types and connectivity in mammalian brain
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fully funded Postdoctoral position to study Alzheimer’s disease and other neurodegenerative disease proteomics signatures. The Cruchaga lab generates and analyzes high-throughput multi-omic data to study
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biostatistical methods to better personalize treatment of cancer patients from deep and diverse types of biomedical information. Analysis of large‑scale clinical, genomic, and molecular datasets. Development and
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., R, Python, SAS, or STATA) Experience working with large population dataset (e.g. EHR, claims data) Background in health informatics, population health research, or biostatistics, computer science
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make a difference in the world! Position Information The Postdoctoral Research Associate is responsible for assisting in the development and application of large-scale modeling frameworks for water and
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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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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 20 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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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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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