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are searching for a motivated and talented Computer Science and Software Engineer to join our Applied Communications team of the Applied Research Laboratory (ARL) at Penn State. This is a software engineering
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, nonlinear dynamical systems, robotics, and formal methods to develop principled models and algorithms for distributed decision-making in complex and uncertain environments. Your research The candidate will
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Brest, Bretagne | France | 15 days ago
Research Framework Programme? Not funded by a EU programme Reference Number 2026-1852/1 Is the Job related to staff position within a Research Infrastructure? No Offer Description Deadline for applications
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). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance portability programming language (e.g., CUDA, HIP, Kokkos, SYCL
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opportunity to collaborate together and learn methods from the parallel project, building a broad skillset. Both positions are part of the larger project “Bringing the wild into the lab with Virtual Reality
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Journal (special issue on Kolmogorov complexity), Vol. 42, No. 4, pp270-283 Wallace, C.S. and D.L. Dowe (2000). MML clustering of multi-state, Poisson, von Mises circular and Gaussian distributions
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computational approaches, including in vivo Massively Parallel Reporter Assays (MPRAs), to define the sequence basis and functional consequences of enhancer activity and to expand MPRA-based approaches to other
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given Tiramisu program, many code optimizations should be applied. Optimizations include vectorization (using hardware vector instructions), parallelization (running loop iterations in parallel
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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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functional genomics, human genetics, and in vivo experimental systems to understand enhancer function across regulatory and phenotypic scales. We develop and apply both experimental and computational