-
training, fine-tuning, evaluation, and experimentation. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background
-
. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background in database systems, including: Relational databases (e.g
-
Details Posted: Unknown Location: Salary: Summary: Summary here. Details Posted: 30-Jun-26 Location: Boston, Massachusetts Type: Full-time Categories: Academic/Faculty Computer/Information Sciences
-
computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background in database systems, including: Relational databases (e.g., PostgreSQL / SQL) Graph databases
-
), including model training, evaluation, and experimentation. Familiarity with distributed or accelerated computing environments (e.g., GPU‑enabled systems, shared compute clusters). Working knowledge
-
, evaluation, and experimentation. Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems). Solid background in database systems
-
programming LAMP stack design and implementation experience Knowledge of GPU and FPGA cluster management Experience with federal research compliance and security requirements Background in AI/ML computing
-
conferences. Qualifications: PhD in computer science with file systems, GPU architecture experience. Proven ability to articulate research work and findings in peer-reviewed proceedings. Knowledge of systems