84 parallel-and-distributed-computing Postdoctoral positions at University of Minnesota
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. Major responsibilites: The candidate will work independently to purify recombinant IDR constructs and label them for F19-NMR analysis. In parallel, the candidate will use Python for bioinformatics
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electrophysiological data sets. Trainees will also have opportunities for clinical exposure through our robust deep brain stimulation and movement disorders clinical research program. Candidates may refer to the below
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in C++/Java/Fortran 90, Python/MATLAB, and MPI-based parallel computing Strong publication record as first author in peer-reviewed journals Preferred qualifications Experience with 3D conjugate heat
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distribution: 50%: Laboratory work involving modern polymer characterization. Maintaining lab equipment. Manifest chemical waste. Troubleshoot instrumentation. Work with undergraduate, graduate, and postdoctoral
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research team to generate, validate, and distribute preclinical mouse models tailored to accelerate validation and therapeutic R&D for emerging gene/protein targets relevant to Parkinson’s disease (PD
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investigating the function of renal afferent nerves in interception. Major responsibilities and approximate distribution of effort. - Rodent surgeries specific to kidney, 10% - Confocal microscopy, 10% - Image
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with the team to conduct a small-scale experimental pilot of the study. The postdoc will be housed inside the Department of Computer Science & Engineering, in the GroupLens lab and collaborate with
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statistical and machine learning, deep learning, chemometrics, multimodal data fusion, computer vision, uncertainty-aware modeling, stochastic control, optimization, and deployable edge-to-cloud decision
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satisfactory performance and the availability of funding. The successful candidate will work with Dr. Yulong Lu on research projects related to the mathematical and computational foundations of generative
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studies focus on the interaction between tumor-intrinsic signaling and the immune microenvironment during adenoma-to-carcinoma progression. A major translational component of the program evaluates