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Field
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machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest ideas using historical
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, statistical analysis, and machine learning techniques to predict market behavior and generate alphas Execution. Create strategies to execute on modelling ideas under simulated competition Evaluation. Backtest
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focus. Example learning problems include exposome and dynamic exposome modeling, learning in timeseries and spatial data, and hybrid deep learning-causal modeling. The successful applicant should have
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advanced molecular/cellular immunology techniques (e.g., multi-parameter flow cytometry, multiplex PCR, IHC, RNA/DNA sequencing, CRISPR editing, Western blotting, and tissue culture). Independently develop
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highly integrated, multidisciplinary approach involving enzyme kinetics, molecular modeling, and biological testing to discover, design, and develop new therapeutics. This position is also anticipated
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 29 days ago
close collaboration at all stages of a research project exploring applications of deep learning and artificial intelligence to dynamic portfolio optimization problems. This position offers the opportunity
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of immunology and molecular biology preferred. Candidates should have excellent scientific writing and strong oral communications skills Experience in leading research papers for publication and data
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and Saeys teams. In this research project you will develop and apply algorithms to link clinical phenotypes of metastasis to molecular phenotypes in mouse models. It is known that metastases exhibit
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strong background in Biochemistry, Chemistry, and/or Molecular Biology. Candidates with expertise in generating, analyzing, and curating large-scale omics datasets, including proteomic, lipidomic
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funding. We are seeking innovative and highly collaborative scientists with a strong background in Genetics, Genomics, and/or Molecular Biology. Applicants with expertise in the curation and analysis