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optimize large-scale distributed training frameworks (e.g., data parallelism, tensor parallelism, pipeline parallelism). Develop high-performance inference engines, improving latency, throughput, and memory
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this changes with age and disease. The successful candidate will contribute to the development and deployment of robust, scalable software solutions that drive our research forward. Your Profile PhD and training
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protein expression and purification, capable of producing thousands of proteins in parallel within weeks . 2) Eukaryotic expression systems facility for production of challenging protein targets. 3) A fully
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. Its human size fosters close interaction between students and lecturers, creating a personal atmosphere. With 1,600 members of academic staff for 6,700+ students and 1,000+ PhD candidates, students feel
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, and the ability to drive and follow through on multiple complex projects in parallel. The Director will collaborate with both internal and external stakeholders to ensure smooth and efficient operations
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models Apply techniques such as quantization, pruning, distillation, sparsity, and parallelism to improve model efficiency Work with deployment tools such as ONNX, TensorRT, cuDNN, vLLM, and SGLang
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The newly established Program for Memory Longevity (PML), led by Attila Losonczy, MD, PhD, in the Peter O’Donnell Jr. Brain Institute (OBI) and the Department of Neuroscience at the University
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the development of both, the quantum internet and distributed quantum computing. The objectives of this PhD thesis project are: (a) Demonstrate spin-photon entanglement with single colour centres in silicon carbide
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of resources, in the context of the REACT MSCA Doctoral Network as Research Associate / PhD student (m/f/x) (You will receive a salary according to MSCA regulation, including a living allowance, a mobility
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Associate Scientist or Lead Researcher - (Protein Engineering and Design, Genome Editing, Biotechnol
evolution. Develop scalable methods to characterize large numbers of CRISPR genome editing variants for activity and specificity with massively parallel high-throughput sequencing approaches. Design and test