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Informatics (DBMI) at Harvard Medical School and the Yu Lab are seeking a Postdoctoral Research Fellow with experience in machine learning and scientific programming. The candidate will work with a multi
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, energy system optimization and possibly machine learning to guide energy transitions towards net-zero systems. The research supervisors have prepared multiple potential projects in this area and will work
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aims to improve electrodialysis (ED) for REE separation by developing advanced membranes and integrating AI-driven optimization techniques. By combining materials innovation with machine learning
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, motivated early-career researcher interested in learning to collect, manage, analyze, and interpret data from multiple systems including mobile eye tracking, motion capture, and force plate posturography as
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including spectral flow cytometry, machine learning and irradiation techniques to generate bone marrow chimera models. Utilize mouse models and patient-derived samples to explore how biological immune aging
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for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. Experts in
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areas. This fellowship places a strong emphasis on the application of machine learning, artificial intelligence, and bioinformatics to solve complex biological problems. Potential research activities may
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
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: Cambridge, Massachusetts 02138, United States of America Subject Areas: Statistics / Machine Learning , Data Science , Statistics Appl Deadline: none (posted 2026/03/16 04:00 AM UnitedKingdomTime) Position
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: Electrochemical process on interface phenomena Battery testing under different conditions Simulation of scaled up process. Interface with machine learning group on data base set up Battery safety testing Presenting