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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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on academic record, as well as professional and extra-curricular experience. Basic Qualifications: PhD in Chemical Engineering, Electrical Engineering, Systems Engineering, Biomedical Engineering or related
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analysis, programming. You aspire to do a PhD in economics / finance later. For the style of research involved in the “Machine learning” track, see the paper “Asset Embeddings ” at https://papers.ssrn.com
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their own research agenda. More information on Professor Dell can be found at this link: https://dell-research-harvard.github.io/ Responsibilities will include: Training and fine-tuning deep learning-based
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-doctoral position in Applied Math. Fellow will conduct research applying machine learning technology to diverse problems in the sciences, aiming in particular at using traditional scientific computing code
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, tissue culture, and protein purification, although we expect to teach all of these while executing projects. Exposure to applicable computer technologies, including specific software applications, may be
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an environment that is diverse, inclusive and respectful. Learn more about our lab here: https://bioniclab.seas.harvard.edu/ We are recruiting fellows from diverse backgrounds interested in solving tough problems
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machine learning methods for computational materials physics and chemistry. Projects include: 1. Scientific software engineering of machine learning potentials for large scale molecular dynamics. We
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of economic decisions. The pre-doc’s task will include designing and implementing experiments; analyzing survey, observational and textual data; and machine learning applications to experimental data
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underlying human diseases, specifically autism spectrum disorders. In this position you will have the opportunity to learn cutting-edge molecular biology techniques, neuronal differentiation of human embryonic