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Field
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disease research, especially involving multi-omic data integration Strong experience with network-based models, especially multiplex or multilayer networks, applied to biological data Familiarity with HPC
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-house CFD software packages. (3) Designing and developing CFD sub-models for application to a broad range of CFD problems. (4) Using high-performance computing (HPC) to accelerate complex, large-scale
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or multilayer networks, applied to biological data • Familiarity with HPC environments is highly desirable • Programming skills in R, Python or equivalent • Excellent communication skills in English
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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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(HPC) international, multidisciplinary environment opportunities for further education and training Hospital-standard social benefits, e.g. jobticket UKF Your challenges: develop, implement, and apply
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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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spatial distribution of critical topsoil properties in global drylands. Process large-scale geospatial and remote sensing datasets using High Performance Computing (HPC) systems. Conduct data analysis, and
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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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. 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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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