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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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modular forms, particularly work with Klein forms and congruences satisfied by Fourier coefficients. Knowledge of special functions and q-series. Ability to deduce combinatorial information from
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perturbation screens with high content molecular and imaging data to understand cellular and multi cellular combinatorial programs in cells and tissues in health and disease. You will join a highly collaborative
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been extensively studied in game theory, reinforcement learning, and optimization, their full integration into modern AI systems (particularly in multi-agent deep learning and human-AI collaborative
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variety of conditions that are not optimal growth conditions. The survival data of pathogens under these conditions (growth matrices + sub-optimal growth temperatures + antimicrobial stresses) will also be
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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other associates to develop optimized photonic test structures that will be incorporated in PIC process flows and enable extraction of key physical parameters associated with PIC performance, including
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and chemoproteomics studies Help develop and apply biochemical, biophysical, and metabolic stability assays Screen compounds; analyze and interpret data Apply data to the iterative design of optimized
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optimization of b-tagging performance for the upgraded tracker. Responsibilities: Conduct independent and collaborative research. The successful candidate will be expected to take a leading role in physics