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. Ubuntu) is essential.. Knowledge of GPU computing, CUDA programming, model optimization, and industry experience in engineering software development would be an advantage. Excellent written and oral
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, Python, CUDA o Open CL) -Manejo de sistema operativo Linux • Proficiency with mathematical software tools such as MATLAB • Strong programming skills (proven experience with programming languages such as
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++. Expertise in ensemble learning (e.g., Random Forests, Gradient Boosting, bagging/stacking frameworks). Hands-on experience with parallel or GPU-based computing (CUDA, OpenCL, or equivalent). Familiarity with
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optimization techniques. You have experience with modern Deep Learning Frameworks (PyTorch, Tensorflow, Jax) and proven ability of CUDA and Python programming. Knowledge of, or prior experience with, optimizing
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(HPC): Experience with parallel computing (MPI, OpenMP, CUDA/HIP) or running workflows on supercomputing clusters. Software Engineering: Knowledge of version control (Git), containerization (Docker
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languages; experience with GPU programming (e.g., CUDA) is highly desirable. Background in optimization, image-guided radiotherapy, medical imaging, or computational modeling. Experience with treatment
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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, convolutional architectures and surrogate modelling for physical systems Solid understanding of PDE-based models or the motivation to acquire this knowledge Experience with real-time or edge deployment (CUDA
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, with experience in additional languages such as Fortran considered a plus. Strong knowledge of at least one parallel programming model commonly used in HPC, such as MPI, OpenMP/OpenACC, CUDA, HIP, Kokkos
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(beyond model training) Solid programming skills (Python required; C++/CUDA a plus depending on simulations) Interest in physics-based simulation, numerical methods, or computational engineering Motivation