Sort by
Refine Your Search
-
Listed
-
Country
-
Program
-
Field
-
computer science or a related discipline. Good knowledge of agentic AI/AI workflows, parallel computing, algorithms, and system performance analysis and optimization. Proficiency in programming languages
-
to closely collaborate with CS faculty members Sriram Pemmaraju and Sourya Roy on sampling problems in the distributed and parallel computing setting. The ideal candidate will have research experience
-
guidance of two experts in computational microscopy and machine learning systems, blending expertise in advanced bioimage informatics and parallel computing: Dr. Min Xu – Affiliated Associate Professor
-
related experience. Unix skills. Experience with scripting and automation (e.g., R, Bash, Python) Understanding of the principles of computer clusters – parallel computing, resource allocation, multiple
-
. Keywords Image processing; Machine learning, Computer vision; Statistical methods; Parallel and distributed computing; Software engineering; Standards; Eligibility citizenship Open to U.S. citizens level
-
parallel codes. Experience with using high performance computing for lattice model simulations. Experience working in a multi-disciplinary research environment. Demonstrated written and oral
-
commercial CFD codes such as STAR-CCM+, ANSYS or COMSOL. Knowledge of finite element simulations methods. Experience using parallel Linux computing platforms, parallel job submission scripts, common
-
massively parallel computing systems, including GPU-accelerated platforms. Develop and maintain scientific software, primarily in Python , using modern practices for software development, testing
-
learning techniques. Adapt computational pipelines for efficient execution on a high-performance computing (HPC) environment, including workflow automation and parallel computing. Apply these computational
-
postdoctoral appointee to develop computational fluid dynamic (CFD) tools that make exascale computing accessible to a broader set of users. The successful candidate will develop a massively parallel