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Solid skills in statistical modeling & probability theory Experience in coding (Python, R, Julia, Matlab...) Motivation to work closely with experimental researchers Curiosity about biological systems
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for wiretap coding. The potential use cases for wiretap codes include Internet of things (IoT) networks featuring short packet payloads, and ultra-reliable low latency communications (URLLC). Research program
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, the accuracy and efficiency of the solution depend critically on how the mesh is distributed relative to the underlying physics. Features such as boundary layers, shocks, vortices, thermal gradients and
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the structure and robustness of the ecological networks supporting reef fish communities at different positions along depth, latitude, and longitude gradients; challenging these networks under hypothesized future
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depth-related plasticity in the physiology and behaviour of mesophotic reef fish. Identifying depth-related changes in the structure and robustness of the ecological networks supporting reef fish
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Biosynthesis (DC12) at the University of Reading, UK. The position is funded by the European Commission through the MSCA Doctoral Network Endotrain (Grant No: 101227148) and coordinated by the University
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, an expert-driven, manual, and time-consuming process used to simplify CAD models so that meshing tools can cope with small-scale features such as fillets and manufacturing details. This de-featuring is not
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the MSCA Doctoral Network Endotrain (Grant No: 101227148) and coordinated by the University of Bergen, Norway. Supervisors: Dr. Luis Fernandez-Luque, Dr. Ana Moro (Adhera Health SL); Prof. Helge Ræder, Prof
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of their health data used for research and treatment purposes at the Faculty of Law, University of Bergen, Norway. The position is funded by the European Commission through the MSCA Doctoral Network Endotrain
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meshing, solver technology, and verification practices. The project is designed to reduce this barrier by creating a practical approach that blends existing industrial strengths in low-order mesh generation