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Field
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, significant coding experience (both Python and C/C++ or P4), and a record of working in a Linux environment and related scripting languages. How to apply Applications for this vacancy are to be made online via
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, bioinformatics, infectious disease epidemiology or a related discipline. Have experience with molecular biology and next-generation sequencing. Have strong computational skills (e.g. Linux, R, Python). An interest
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sequencing is highly preferred · Experience with single-cell data analysis · Proficient in Linux/Unix-based high-performance computing (HPC) environments and job schedulers (e.g., SLURM or qsub
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interfacial reaction mechanisms demonstrated proficiency in DFT and at least one major electronic-structure package (for example VASP, Quantum ESPRESSO, CP2K, GPAW or equivalent) strong Python, ASE, Linux/HPC
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, computational biology, genomics, or a related quantitative field. You will have strong programming skills (Python, R, Linux) and experience analysing large-scale sequencing datasets, ideally RNA-sequencing data
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of application. Strong mathematical skills and significant programming experience (e.g. Fortran, Matlab, Python, Linux). Significant experience in numerical modeling and familiar with at least one of
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-dimensional genomic datasets. Strong programming skills in Python and/or R, and experience with Linux/HPC computing environments. Experience with single-cell RNA-seq, single-nucleus RNA-seq, sc/snATAC-seq
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potentials or force fields (for example MACE, NequIP, DeePMD). ● Experience running scientific calculations on Linux-based high-performance computing clusters, including scripting or workflow automation
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understanding of experimental design and statistical methodology. Experience with Linux/Unix environments, command-line tools, and computational workflows. Experience with data visualization using R, Python
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, environmental engineering, or a related field. Experience in numerical hydrologic models and land surface models. Experience with Linux on cluster and/or high-performance computing environments. Experience