Sort by
Refine Your Search
-
Listed
-
Employer
- Oak Ridge National Laboratory
- Argonne
- Harvard University
- SUNY Polytechnic Institute
- University of Nebraska Medical Center
- University of Utah
- Brookhaven National Laboratory
- Duke University
- Embry-Riddle Aeronautical University
- Northeastern University
- Rutgers University
- Texas A&M University
- University of Miami
- University of New Hampshire – Main Campus
- University of North Carolina at Chapel Hill
- 5 more »
- « less
-
Field
-
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
-
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
-
mathematicians, and domain scientists Develop software that integrates machine learning and numerical techniques targeting heterogeneous architectures (GPUs and accelerators), including DOE leadership-class
-
in top-tier machine learning/AI conferences and/or leading scientific journals. Excellent programming skills and hands-on experience with leading machine learning frameworks (e.g., TensorFlow, PyTorch
-
: Knowledge on floating point arithmetic and mixed/reduced precision computing techniques Experience with programming GPUs and/or other accelerators Proficiency in mathematical reasoning and numerical analysis
-
). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative AI methods as
-
University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 6 hours ago
. The researcher(s) will be provided access to state-of-the-art supercomputing facilities with advanced GPU and data storage capabilities. Additionally, opportunities will be available for collaborations. Duties
-
in top-tier machine learning/AI conferences and/or leading scientific journals. Excellent programming skills and hands-on experience with leading machine learning frameworks (e.g., TensorFlow, PyTorch
-
Science, or a related field Strong programming skills in Python, R Solid understanding of: Machine learning fundamentals Deep learning architecture (e.g., CNNs, RNNs, Transformers) Optimization and model
-
Mathematics, or a related quantitative discipline. Strong programming skills in C++, Python, MATLAB, or similar languages; experience with GPU programming (e.g., CUDA) is highly desirable. Background in