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science, with a particular focus on neuroscience applications. Designs AI techniques and algorithms for multimodal data fusion (e.g., MRI, EEG, cognitive and behavioral data, blood biomarkers, and
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postdoctoral position is available in the Geometric Machine Learning Group at Harvard University, led by Prof. Melanie Weber. This role offers an opportunity to perform research at the intersection of Geometry
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)colonial Indigenous settings in the USA. Responsibilities Under the supervision of Prof. Joseph Gone, Faculty Director of the Harvard University Native American Program, and in collaboration with regional
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. Led by Prof. Usama Fayyad, the Institute for Experiential AI is built around the
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Condensed Matter Physics and Materials Sciences o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph
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, Algorithm, Extremal Graph Theory, Computing Theory o Programming Language, AI Theory or Machine Learning o Classical and Quantum Algorithm for Computational Quantum Many-body Theory o Theory and Computation
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-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements. § Implementing algorithms
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additional skills are not required, but may help. Department Contact for Questions Questions regarding the position or application process can be directed to: Prof. Alexandru B. Georgescu, Department
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designs and methods, clinical trial methods, Bayesian methods, and developing R packages and scalable algorithms. Opportunities for collaboration across the Department of Biostatistics and the Medical