66 parallel-and-distributed-computing-phd positions at Chalmers University of Technology in Sweden
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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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specialise in nanoparticles formulated from lipids. We characterise the composition and distribution of lipid molecules in both synthetic and naturally occurring nanoparticles (including extracellular vesicles
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of managing reverse logistics for returned products, and the potential disruptions to existing distribution networks. About us and the research project The division of Supply & Operations Management (SOM
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, you must hold a PhD (awarded no more than three years prior to the application deadline*) in computer science, maritime transportation, or a related field, with a strong foundation in mathematics and
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-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality
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facilities that are highly aligned with the goals of the project. Who we are looking for We seek candidates with the following qualifications: To qualify for the position of postdoc, you must have a PhD degree
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to develop solutions with real world relevance and impact. This project will be carried out in close collaboration with researchers from the Division of Material and Computational Mechanics at IMS and the
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This postdoc project aims to address a critical challenge in quantum computing: errors in superconducting qubits caused by cosmic radiation, which cannot be corrected using existing methods
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of a unique and collaborative research environment in micro- and nanotechnology, housing over 250 researchers and PhD students. The main research activities at the terahertz and millimetre wave
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institutes and industry partners play a key role in our work. Our group currently includes 1 Professor, 1 Senior Scientist, 4 Postdocs and 8 PhD students. Your research will focus on significantly reducing