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: Documented experience in the development and optimization of scientific software for GPU-based computing platforms. Experience with programming using CUDA, HIP, SYCL, OpenACC, or equivalent technologies
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activities in areas such as numerical analysis, mathematical modelling, development and analysis of algorithms, machine learning, optimization, scientific software development and high-performance computing
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areas such as machine learning, optimization, scientific software development and high-performance computing. The division is an important part of the eSSENCE e-science collaboration and of the Science
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extension. Project description: The purpose of the project is to pursue research in pancake sorting, which is a well-known problem in combinatorial optimization which goes back up to a paper of
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employment with a maximum period of 3 years. The main responsibility of this position is to contribute to research projects focusing on modelling, optimization, control, and AI applications for smart
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catalysis and reactor system optimization for sustainable energy and chemical conversion. The research will explore the integration of electrochemical processes with enzymatic catalysis for the selective 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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tightly coupled to GPU-accelerated high-performance computing using Lund University’s national e-infrastructure. You will join an interdisciplinary research environment that values scientific independence
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productivity optimization. For this position, mathematical, analytical and problem-solving skills are essential in order to understand and benefit from this new data intensive mining environment. Duties As
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protein complexes, cryo-EM sample preparation and grid optimization, as well as processing and structural analysis of cryo-EM data. Structural findings will be combined with in vitro biochemical analyses