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the AliceVision library. Activity 3: Critical Code Optimization (C++/CUDA) - Adapt the code to drastically reduce computation times (target: < 1h). - Replace proprietary dependencies (InstantNGP) with a flexible
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the AliceVision library. Activity 3: Critical Code Optimization (C++/CUDA) - Adapt the code to drastically reduce computation times (target: < 1h). - Replace proprietary dependencies (InstantNGP) with a flexible
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Postdoc (f/m/d) on Generative AI for de Novo Protein Design / Completed university studies (PhD) ...
to work in a collaborative multidisciplinary environment # Excellent programming skills in languages such as Python, C/C++ and CUDA # Familiarity with modern deep learning frameworks like Tensorflow 2.x.x
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their publications Experience programming GPUs with CUDA, SYCL, HIP or OpenMP Experience using and developing code with AMReX Experience in performance engineering to improve code scalability and reduce time-to
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frameworks, e.g., Caffe, TensorFlow, PyTorch, and GPU-acceleration frameworks, e.g., CUDA will be a plus. Outstanding SW development and programming skills in C++, Python, ROS tools and libraries. Excellent
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, and/or quantum chemistry Cuda, TensorFlow Familiarity with common tools for structure-based molecular modeling or virtual Experience developing or benchmarking computational methods for drug discovery
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, CUDA or equivalent), is expected. The demonstrated ability to tackle multiscale problems and to contribute to the development of innovative imaging prototypes is highly desirable. 3) Familiarity with
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++, Rust, or similar languages. CUDA experience is a plus. Passion for interdisciplinary research in an innovative and collaborative environment. Application Process: Submit your CV, cover letter, and
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written and oral communication skills. Experience with MPI, OpenMP, parallel I/O (including HDF5), CUDA and/or OpenACC, Fortran, C++, Python. Motivated self-starter with the ability to work independently
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++ and CUDA) Code verification and validation of simulations Providing simulation results to project partners and customers Active participation in project, group and lab meetings, knowledge transfer