Assistant Computational Scientist
@ Brookhaven National Laboratory

Upton, NY
$138,000
On Site
Full Time
Posted 1 day ago

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Job Details

Overview

Brookhaven National Laboratory is seeking an Assistant Computational Scientist to join the CDS Computational Science Department. This role focuses on designing, developing and integrating computational techniques for scientific applications.

Key Responsibilities

  • Collaborate with interdisciplinary teams of scientists, mathematicians and engineers.
  • Conduct innovative research in high performance computing, machine learning and quantum computing.
  • Develop and implement novel software and numerical methods.
  • Present research findings at meetings, workshops and conferences.
  • Contribute to research grant proposals and mentor junior staff.

Position Requirements

Candidates should have a strong background in computational science with proven research experience. Required qualifications include a relevant degree with corresponding years of work or research experience, demonstrated programming skills in C/C++, Python, Fortran or similar languages, and experience in high performance computing environments.

Preferred Qualifications

Additional experience with GPU accelerators (CUDA, HIP, SYCL, etc.), distributed parallel computing (MPI, NCCL), complex workflow management, and applying artificial intelligence in scientific domains is desired.

Other Information

This is an on-site position located in Upton, NY. Moderate domestic and international travel is expected. Detailed benefits information and site access requirements (REAL-ID compliant documentation) apply.

Key skills/competency

Computational Science, High Performance Computing, Machine Learning, Numerical Methods, Software Development, C/C++, Python, Research, Simulation, Interdisciplinary

How to Get Hired at Brookhaven National Laboratory

🎯 Tips for Getting Hired

  • Customize your resume: Highlight computational research and programming experience.
  • Align with requirements: Emphasize HPC and machine learning skills.
  • Showcase projects: Include relevant simulation and numerical methods work.
  • Prepare for interviews: Review research contributions and technical challenges.

📝 Interview Preparation Advice

Technical Preparation

Review HPC and machine learning concepts.
Practice coding in Python and C/C++.
Study numerical methods and simulation techniques.
Familiarize with parallel computing tools like MPI.

Behavioral Questions

Describe teamwork in interdisciplinary research.
Explain handling research setbacks.
Discuss collaborative project experiences.
Share communication strategies in diverse teams.

Frequently Asked Questions