美国布鲁克海文国家实验室博士后—辐射探测与机器学习

美国布鲁克海文国家实验室博士后—辐射探测与机器学习

布鲁克海文国家实验室(BNL)位于纽约长岛萨福尔克县（SUFFOLK COUNTY）中部，隶属美国能源部，由纽约州立大学石溪分校和BATTELLE成立的公司布鲁克海文科学学会负责管理。该实验室成立于1947年，历史上该实验室曾经有7个项目获得过诺贝尔奖。

Postdoc in Radiation Detection and Machine Learning Upton, NY

Brookhaven National Laboratory

Postdoc in Radiation Detection and Machine Learning

Job ID 3438 Date posted 11/03/2022

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.

Position Description

The Nonproliferation and National Security Department seeks a 2-year term postdoctoral Research Associate with knowledge and experience in machine learning and its applications in nuclear engineering, national security, nuclear safeguards, or relevant fields. The successful candidate will participate in ongoing research in machine learning for radiation measurements, nuclear safeguards, and security, and is expected to contribute to future proposals to develop new research opportunities. This position has a high level of interaction with an international and multicultural scientific community and will be expected to give presentations at BNL lectures, conferences, and project review meetings to discuss research results.

Essential Duties and Responsibilities:

Apply machine learning to data analysis in radiation detection and nuclear security and safeguards to improve operational performance and efficiency

Conduct research in machine learning focusing on applications of radiation detection in nuclear security, nuclear safeguards, and healthcare

Develop machine learning algorithms and software tools to meet sponsors' operational needs

Position Requirements

Required Knowledge, Skills, and Abilities:

PhD in any one of the following; Nuclear Engineering, Applied Math, Computational Science, or related field

Familiarity with machine learning fundamentals, techniques, and applications

Demonstrated programming skills in Python

Experience with accelerators (GPU and/or FPGA) and high-performance computing systems

Clear and concise oral and written communication and presentation skills

Ability to work closely and communicate effectively with domain and infrastructure scientists

Strong track records of publication

Preferred Knowledge, Skills, and Abilities:

Familiarity with deep learning libraries (Theano, Torch, Caffe, TensorFlow, etc.)

Demonstrated algorithm development and deployment experience in national security, nuclear safeguards, and/or nuclear engineering

Working experience in deep learning algorithms for object detection/classification/tracking and/or natural language processing

Track record of producing high-quality software on schedule

Experience working in multidisciplinary scientific collaboration

Environmental, Health & Safety Requirements:

The main scope of work will take place in an office environment as well as in the laboratories. The successful candidate must be able to conduct the activities safely in BNL laboratories by completing required training, interpreting laboratory safety information postings, and wearing appropriate personal protective equipment.

准备申请国外博士后的各位老师注意了！知识人网（www.zsr.cc）小编每周定时更新最新的国内外博士后招聘信息以及访问学者、博士后资讯，感谢大家的关注！