Why Work at BNL?
Brookhaven National Laboratory is a multipurpose research institution funded primarily by the U.S. Department of Energy's Office of Science. Located on the center of Long Island, New York, Brookhaven Lab brings world-class facilities and expertise to the most exciting and important questions in basic and applied science--from the birth of our universe to the sustainable energy technology of tomorrow. We operate cutting-edge large-scale facilities for studies in physics, chemistry, biology, medicine, applied science, and a wide range of advanced technologies. The Laboratory's almost 3,000 scientists, engineers, and support staff are joined each year by more than 4,000 visiting researchers from around the world. Our award-winning history, including seven Nobel Prizes, stretches back to 1947, and we continue to unravel mysteries from the nanoscale to the cosmic scale, and everything in between. Brookhaven is operated and managed by Brookhaven Science Associates, which was founded by the Research Foundation for the State University of New York on behalf of Stony Brook University, and Battelle, a nonprofit applied science and technology organization.

Organizational Overview

Brookhaven National Laboratory (BNL) is a scientific, extreme scale Data Laboratory in the US, New York State, Long Island. We support the data and computational needs of on-site facilities such as the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source II (NSLS II), the Center for Functional Nano Materials and the Atmospheric Radiation Measurement program. In addition we host the largest data center for the ATLAS experiment at CERN, and provide online and offline data services for the Japanese Belle II experiment. With over 170 PB of archived data BNL hosts one of the top 10 scientific data archives in the world, in 2019 alone we analyzed over 800 PB of scientific data.

As a result, we have a lively, fast-growing data science research program at BNL, with a specific focus on the challenges presented by the analysis, interpretation, and use of data at extreme scales and in real-time. The data science program is accompanied by significant computational modeling research effort, in support of the design, planning, analysis, and interpretation of experiments and their results. The Computational Science Initiative (CSI -https://www.bnl.gov/compsci/) provides a laboratory-wide umbrella for these activities, bringing together computer scientists, applied mathematicians, and domain scientists to carry out leading-edge research, convert research results into practical solutions that advance domain science, and provide the necessary computing infrastructure services and training to support efficient operation.

Position Description

CSI is currently looking for a postdoctoral researcher to join our AI and machine learning group. The successful candidate will conduct research to explore how machine learning can be applied in various science applications including bio-medical science, chemistry, etc. We will expect you to be able to work successfully in a multidisciplinary team.

Essential Duties and Responsibilities:

• Perform data analysis of bio-medical science and other interdisciplinary science area
• Identify potential challenges of applying existing machine learning methods
• Improve existing data analysis methods or develop novel learning algorithms
• Perform evaluation of learning algorithms
• Implement existing or developed methods in HPC environment

Position Requirements

Required Knowledge, Skills, and Abilities:

• Ph.D in computer science, math, statistics or related discipline is required.
• Proven ability for disseminating research results by writing manuscripts and giving academic presentations.
• Candidates must be willing to travel in order to disseminate results and communicate with other scientists.
• Programming skills are essential along with in depth knowledge of online data analysis.
• Written and oral communication skills.
• Ability to work closely and communicate effectively with other domain scientist and infrastructure scientist.

Preferred Knowledge, Skills, and Abilities:

• Worked with general ML libraries and toolkits including PyTorch
• Experience with large scale data analysis
• Experience working in multidisciplinary scientific collaboration
• Experience with OpenMP, MPI, OpenACC, OpenCL, etc.
• Experience with accelerators (GPU, Intel Xeon Phi) and high performance computing systems
• Track record of producing high quality software on schedule

OTHER INFORMATION:

• Moderate domestic and foreign travel
• The initial appointment will be for two years, with annual renewal contingent upon satisfactory performance and continued funding.
• This position is mainly working on bio-medical domain.

• Medical Plans
• Dental Plans
• Vacation
• Holidays
• Life Insurance
• 401(k) Plan
• Paid Parental Leave
• Swimming Pool, Weight Room, Tennis Courts, and many other employee perks and benefits