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Field
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data, in particular single cell data and/or spatial data Experience in method development Experience working on servers and/or in a HPC environment Personal qualities We are looking for a researcher who
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of the candidate: PhD in atmospheric sciences or a closely related field The candidate should have experience in climate model development and assessements A strong programming background and use of HPC are required
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for applying to the University of Luxembourg and its HPC Certified copies of degree certificates, incl. a transcript of courses taken (with grades) Names and contact details of three referees Early application
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will play a pivotal role in advancing research in artificial intelligence (AI), energy-efficient computing, foundational mathematical models, high-performance computing (HPC), dimensionality reduction
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modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
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exchange and interaction state of the art computing infrastructure (HPC) salary assigned according to the pay scale UKF standard social benefits, e.g. UKF job ticket UKF Your tasks: develop and optimize
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. Familiarity working with publicly available genomics data and working in high-performance computing (HPC) and/or UNIX environments is a plus. Highly motivated, able to creatively take initiative to see your
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/interest with or prior experience working with NGS algorithms such as PLINK, or experience working in a cloud computing environment or UNIX/linux/HPC cluster. Department Contact for Questions Dr. Bohdan
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modelling, preferably WRF Experience of scientific programming and running code on HPC systems Experience with Fortran, Python and Linux Shell Any of the following is advantageous but not essential
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learning packages (e.g. PyTorch, Keras) Experience with HPC and scientific workflow management tools (e.g. Nextflow, Snakemake) Experience with single-cell data analysis (e.g scanpy, scvi), and/or spatial