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Field
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HPC clusters. Experience of modern computational statistical methodologies, such as Markov chain Monte Carlo, rejection sampling, sequential Monte Carlo, would be highly desirable. Attributes and
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. Bioinformatics: Comparative genome analysis, detection of selection, and functional genomics, phylogenetics. Computational skills: UNIX/Linux, HPC computing, and programming in R and Python. You will gain hands
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, and cloud or HPC environments. Additional Information: In keeping with its access, excellence, and impact mission, The University of Texas at El Paso is committed to an open, diverse, and inclusive
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visualization. Expertise in data processing and analysis using HPC and Galaxy platform and familiarity with widely used, and field standard software, webtools and packages, including HISAT2, Salmon, Rsubred
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, Birkbeck), the Protim proteomics platform, and the HPC Jean-Zay supercomputer (GENCI). Title Deciphering the molecular mechanisms of substrate recruitment in the Type IV Secretion System using
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into concrete tractable problems you can solve. Be equally passionate about rigorous mathematical reasoning and hands-on Python implementation (PyTorch, JAX, …) in HPC environments. Communicate clearly in English
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control and cloud/HPC computing platforms. Familiarity with containerization (Docker). Ability to collaborate with multidisciplinary teams (e.g., biologists, clinicians, software engineers) and to
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] method within the MiMiC multiscale simulation framework Develop and integrate a communication interface between quantum computers (via Qiskit) and classical HPC resources Validate the QCS-MiMiC
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qualifications: Experience in running large-scale analyses on Linux-based HPC clusters using job schedulers (e.g., Slurm) and/or on cloud research platforms (e.g., DNAnexus/AWS). Experience in analysing high
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of work: low-resolution algorithms, model optimisation with HPC techniques, edge computing, quantum computing, energy-efficient compact data structures, NLP optimisation. Justification of duration A