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cell- and module level. Particular emphasis will be placed on leveraging modern heterogeneous computing architectures to enable large-scale, high-fidelity reacting-flow simulations. The models developed
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time-series data Experience of high-performance computing, GPU-based computing, or parallel programming Experience of probabilistic modelling or inverse problems Experience of developing and
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scientific computing, image analysis and research infrastructures, you will collaborate closely with scientists, software engineers, beamline scientists and computing specialists across the European
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aims to turn HTC filtrate from a problem into a resource. In parallel, the filtrate is used as substrate for microbial production of biodegradable plastics (PHA) together with our partners at Karlstad
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courses at the department each year. You can find more information about us on the Department of Information Technology website. The position is hosted by the Division of Scientific Computing (TDB
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Information Technology website. The position is hosted by the Division of Scientific Computing (TDB), one of the world’s largest research environments in computational science, with large activities in
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in English. Strong collaborative skills and the ability to work systematically with several stakeholders and parallel activities. The following experience is particularly advantageous: Implementation
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transcription such as ChIP and RIP-seq you are self-motivated, persistent and collaborative with an analytical mind and capacity to structure more than one project in parallel you have the ability to
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parallel. Active participation in other ongoing projects in the lab and clear communication of research findings to both specialized and general audiences are expected. Additional responsibilities include
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partners. Tasks and responsibilities You will conduct computational research involving Python programming and high-throughput protein structure prediction using high-performance computing infrastructure