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computational science, collaborating with leading European research groups and benefiting from advanced GPU and HPC infrastructure. Where to apply Website https://www.academictransfer.com/en/jobs/359110/postdoc-2
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INGEGNERIA INDUSTRIALE | Italy | 26 days ago
Description Analysis and development of methodologies to accelerate the computation of numerical optimization through parallelization and the use of GPUs. Where to apply Website http://www.unibo.it Requirements
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transferability. Data pipelines for structured and unstructured data (images, text, social media, retail data) will be designed and validated on real-world case studies. Where to apply Website https
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Job Code 0005 Employee Class Civil Service Add to My Favorite Jobs Email this Job About the Job The successful applicant will assist in the adaptation of the PPMstar code to run well on GPU-accelerated
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frameworks (PyTorch, TensorFlow). Experience with dataset curation, annotation workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data
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, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized knowledge of Neural Rendering (NeRF/3DGS) or Satellite Photogrammetry. Demonstrated
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bioimaging and bioinformatics team at IBENS, under the supervision of Auguste Genovesio. The postdoctoral researcher will have access to a workstation as well as computing servers equipped with GPUs. Where
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frameworks (e.g., PyTorch). Familiarity with GPU-accelerated environments, virtualization tools, and prototyping using real testbeds (e.g., SDR). We expect a diploma in computer science or telecommunication
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specialists and set clear priorities to realize projects effectively and on time, building infrastructure that makes complex analyses faster and more efficient. Your team optimizes virtual computing power (GPUs
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highly-motivated candidate, skilled in numerical model development (programming in FORTRAN, numerical methods, HPC environment). Experience in numerical methods on unstructured grids and/or GPU would be