-
, enhanced sampling, QM/MM) Experience improving performance and scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation
-
researchers Grant writing experience Experience with high performance computing (HPC) and deep learning frameworks like PyTorch Experience developing parallel algorithms and scalable workflows for HPC resources
-
. Formulating necessary solutions using various parallel computing paradigms and tools, HPC schedulers (such as slurm), Containers and Kubernetes, Python, Bash and other scripting/programming languages in
-
in multiphysics modeling Experience in parallel programming on large-scale computational clusters Expertise in Matlab programming Active TS/SCI Clearance is preferred Special Requirement: This position
-
). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance portability programming language (e.g., CUDA, HIP, Kokkos, SYCL
-
, and parallel computing, with a proven ability to work within highly secure and regulated environments. This role involves close collaboration with security teams, scientists, and IT leadership to ensure
-
strategic management and strict adherence to security protocols. We are looking for candidates with extensive experience in either classified HPC data center operations, architecture, parallel computing
-
, chunking, parallelization; Dask/Spark a plus). Experience using or building agentic/LLM-enabled workflows for data discovery, extraction, and normalization, with attention to provenance, reproducibility, and
-
environments. Leverage cloud object storage (e.g., Amazon S3) for data staging and artifacts; implement parallel, secure data movement and lifecycle policies. Basic Qualifications: Ph.D. in Computer Science
-
systems. Expertise with batch schedulers (SLURM, PBS, LSF) and parallel file systems (Lustre, GPFS/Spectrum Scale). Proven ability to lead technical projects from concept through implementation, balancing