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) for reproducible research workflows. Support Optimising GPU-accelerated workloads (e.g., PyTorch, TensorFlow), including multi-GPU scaling and distributed training. Develop training materials, documentation, and
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shaping and imaging Proficiency in GPU programming (CUDA/OpenCL) and strong coding skills in C/C++ and Python Practical experience with Spatial Light Modulators (SLMs) and wavefront shaping techniques Solid
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datasets. The Research Associate will: Design and implement high-performance workflows integrating GPU programming, deep learning, and large-scale data integration. Apply advanced methods such as ColabFold
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pipelines for large-scale biological datasets. The Research Associate will: Design and implement high-performance workflows integrating GPU programming, deep learning, and large-scale data integration. Apply
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likely to be required include advanced Python or c++ with experience in developing and fine-tuning foundation models for modelling tasks, including use of HPC systems and multi-GPU programming. Knowledge
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learning frameworks such as PyTorch, JAX, or TensorFlow. Experience with C++ and GPU programming. A strong growth mindset, attention to scientific rigor, and the ability to thrive in an interdisciplinary
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healthcare datasets, such as MIMIC, EHRs, or other health information systems. Proficiency in SQL, Python, or other programming languages used for data manipulation and ETL processes. Experience with cloud