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tested by isothermal titration calorimetry (ITC) or microscale thermophoresis (MST) in collaboration with the lab of Prof. Andy Lovering. In parallel, minibinder/effector pairs will be co-expressed using
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optimizing and parallelizing workflows to run on compute clusters. This position is ideal for someone who is looking to gain research experience, enhance their technical skills, or is considering graduate
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other research services and resources. Strong programming skills in languages such as C, C++, Fortran, Python, or other languages commonly used in HPC environments. Deep understanding of parallel
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algorithm development and application. Familiarity with common scientific programming languages such as C++. Experience in parallel programming with one or more common parallel programming models, like MPI
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Requirements: The candidate must be able to demonstrate a deep knowledge of supercomputing software development for massively-parallel computer architectures, and expertise in working with large-scale software
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- and neuron-targeting anti-obesity drugs in these ex vivo systems. In parallel, you will collaborate with a team of postdocs, PhD students, and technicians working with genetic animal models
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computational, molecular and biophysical techniques. During the project you will design the methodology for, and perform the directed evolution of H-transfer enzymes using parallel selection methods, measure
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and optimization strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data
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activation processes catalyzed by transition metals. In parallel, we work on the design and synthesis of bifunctional compounds for selective catalytic reactions. In particular, we are interested in
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, and parallel computing, with a proven ability to work within highly secure and regulated environments. This role involves close collaboration with security teams, scientists, and IT leadership to ensure