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, cancer genomics, or a related field. Applicants with a background in biology or (bio)medicine are welcome to apply, provided they have documented expertise in deep learning Proficiency in programming
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Boltzmann method (LBM), discrete Boltzmann method (DBM), and other kinetic models. Solid knowledge of fluid dynamics and heat transfer. Proficiency in programming languages such as C/C++, Fortran, Python
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
, or related fields Strong programming skills in Python, R, and experience with Linux environments Demonstrated experience in processing and analyzing large-scale genomic and transcriptomic datasets
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proteins to specific locations on the genome. The project involves grid preparation and screening, data collection and image processing using the Emory cryoEM core and our lab’s cluster (200 TB and 8 GPU
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++ and Python programming languages. Experience in open source projects, GPU programming, distributed computing and cloud computing are considered to be strong assets. The position of Research Fellow at
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for earth system science C++ programming skills and model simulations on GPUs E3SM, CESM, and WRF model experience Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term
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experimental data. Experience in GPU programming. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is
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experience with coding in C++, python/matlab. GPU programming is a definite plus. You have experience in applying deep learning to solve computational imaging problems. Experience with inverse problems such as
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allowance. Generous travel, equipment, and publication funds. Access to NYUAD’s world-class research facilities, including a high-performance computing (HPC) cluster with ~30,000 cores and 34 GPU nodes. Start
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electricity prices with focus on Nordic electricity market including implementation, test and validation at the DTU Risø HPP facility (possibly in a GPU computing infrastructure) Aid the implementation of IEA