7 multiple-sequence-alignment Postdoctoral positions at Harvard University in postdoctoral
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aim to advance the capability and applications of this technique to demystify activity at complex electrodes across multiple length scales (nano- to macro), enable new types of measurements, achieve
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Education and the Curriculum Fellows Program to align and strengthen the postdoc RCR course and the graduate student Responsible Conduct of Science (RCoS) course. Other tasks as assigned Physical Requirements
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Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
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for analysis of large-scale whole genome genetic and genomic and phenotype data. Examples include large Whole Genome Sequencing association studies, biobanks, single-cell and CRISPR multiome data, integrative
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. The position will be supervised by Professor Francesca Dominici and will focus on building and evaluating a decision framework to guide the expansion of AI data centers, aligning economic opportunity with social
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, ● Methods for heterogeneous treatment effects estimation, ● Methods for multiple exposures, multiple outcomes, ● ML and AI methods for causal inference, ● Bayesian causal inference, ● methods
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multiple faculty members. Candidates for this position must have completed their Ph.D. degree by the appointment start date; demonstrate outstanding research in theoretical condensed matter physics