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Field
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multiscale simulation methods for quantum mechanical properties of macromolecules, developing novel ways to combine quantum chemical methods and machine learning, developing quantum algorithms
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dynamics (algorithms and current practice). Experience in AI/ML. Experience in application performance optimization. Familiarity with parallel programming models (e.g., OpenMP, MPI, CUDA). Experience
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genetic knockouts in yeast and mammalian cell lines, and protein purification. Job Responsibilities: 35%: Computational algorithm development and data analysis 35%: Design and conduct experiments with yeast
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biology or related field Experience with omics data analysis (e.g. transcriptomics, metabolomics) Knowledge of machine learning/deep learning algorithms Knowledge of systems biology approaches (e.g. genome
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Pharmaceutical health outcomes, (Pharmaco)epidemiology, Biostatistics, or a related field. · Expertise in or a strong interest in machine learning and deep learning algorithms. · Excellent communication skills
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experience from which comparable knowledge is demonstrated may be considered. Preferred Qualifications Ph.D. degree. Demonstrated expertise in computational biophysics and molecular dynamics (algorithms and
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and implement power grid planning/operations algorithms and tools and conducts data analysis related to energy and power systems, with emphasis on the following areas: Variable energy resource
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Apply Now Responsibilities* Conduct research focused on designing and implementing algorithms related to cryo-electron microscopy (cryo-EM) data collection in a lab that focuses on the structural
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of Applied Psychology. Current faculty conduct research on a wide range of topics pertaining to the future of work, including entrepreneurship, collaboration, remote working, labor markets, algorithms, machine
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analysis and algorithm implementation for high-throughput sequencing data. Act as a liaison between end-users, software developers, system designers and different departments. Oversee quality check for high