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-throughput screening, and online/in situ characterization with active-learning and Bayesian-optimization pipelines to guide experiment selection Build agentic artificial intelligence (AI) workflows and FAIR
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determinants of health. The focus of this role is on cognitive decline and dementia, with an emphasis on: Applying epidemiologic, econometric, and other methods to strengthen causal inference Working with
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on the design and development of mathematical, probabilistic, and statistical frameworks for drawing inferences from complex biological data in collaboration with scientists at the Snow Centre for Immune
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-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
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track record in one or more of the following areas, or a combination of these areas: Knowledge-grounded artificial intelligence and knowledge graphs, including large language model (LLM) and retrieval
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, and participation tracking Administer assessments and manage the merging, cleaning, and quality control of survey, assessment, and administrative data Conduct quantitative analysis of skill growth and
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field. Strong candidates will have a track record of research in peptide quantification and analysis (LC-MS/MS, HPLC, or equivalent), experience studying peptide-immune cell interactions, microbiome
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, Cell and Molecular Biology, Biology or a related field. Strong candidates will have a track record of research in rodent behavioral testing, proficiency in CNS analysis, including histology of brain
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track record of research in rodent behavioral testing, proficiency in CNS analysis, including histology of brain sections, demonstrated skill in stereotaxic injections, human cerebral organoid models, use
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written and oral communication skills and demonstrated ability to write peer reviewed quality work or invention disclosures for patent applications, technical reports. Consistent track record