Automated Cataloging of 2D MaterialsJob ID 2775 Date posted 08/31/2021
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 premier facilities and expertise to the most exciting and meaningful questions in basic and applied science—from the birth of our universe to the sustainable energy technology of tomorrow. We operate state-of-the-art large-scale facilities for studies in physics, chemistry, biology, medicine, applied science, and a wide range of advanced technologies. Brookhaven Lab employs nearly 3,000 scientists, engineers, and support staff, and engages more than 4,000 visiting researchers from around the world each year. 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. Brookhaven Science Associates, a nonprofit applied science and technology organization, operates Brookhaven Lab for the U.S Department of Energy.
The CFN is seeking a Scientific Associate to work on a collaborative project to develop methods and software for a unique autonomous experimental platform. The CFN is building an integrated set of advanced tools to streamline synthesis and handling of two-dimensional (2D) materials; and in particular seeks an accomplished scientist to enhance the capabilities of an automated multi-modal microscope used to identify and classify 2D material flakes on surfaces. Your work will combine software development for instrument control and automation, data analysis pipelines for image recognition tasks, and machine-learning methods for classification and prediction. You will combine software skills with knowledge of ultrathin materials to implement physics-informed methods, and participate in the design of a domain-specific database. You will deploy multi-modal image recognition methods into an active research environment. You will collaborate with other project colleagues to integrate new methods into the overall platform.
Roles and Responsibilities
- You will improve instrument control software, developing iterative multi-modal scanning of samples.
- You will develop improved image segmentation, recognition, and classification code, leveraging machine-learning methods where appropriate, to robustly identify 2D flakes.
- You will leverage materials knowledge and measurement physics knowledge to develop domain-specific analysis modules.
- You will participate in the design of a domain-specific database, including curation and annotation of datasets.
- You will demonstrate the viability of developed methods by integrating them into the experimental platform, and working with other team members to automatically scan and classify samples.
Required Knowledge, Skills, and Abilities:
- You have earned a B.Sc. degree in Physics, Materials Science, Electrical Engineering, or a suitable related discipline;
- You are knowledgeable in measurement and synthesis/handling applied to ultrathin (2D) materials;
- You have experience with scientific programming using the Python language and some of the associated libraries (numpy, scipy, matplotlib, OpenCV, skimage, sklearn, etc.);
- You have deployed software for hardware control and/or data analysis into materials research projects;
- You deliver effectively on project goals and milestones, including working as part of a collaborative team;
- You are committed to fostering an environment of safe scientific work practices.
Preferred background and experience:
- You have minimum 2 years of additional technical experience outside of B.Sc. education, such as research training towards a Masters or Ph.D. degree, or technical work in a production environment;
- You have experience with advanced analytics approaches, especially machine-learning methods for image registration, feature detection, segmentation and classification;
- You have experience with multi-modal imaging/measurement instruments, especially modalities suitable for 2D materials (optical microscopy, Raman spectroscopy, AFM, STM, photoluminescence, etc.);
- You have direct experience researching mechanical and/or optical properties of 2D material flakes;
- You communicate effectively, especially in scientific discussions and in delivering technical documentation.
- Medical Plans
- Dental Plans
- Life Insurance
- 401(k) Plan
- Retirement Plan
- On site swimming pool, weight room tennis courts, and other employee benefits
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BNL takes affirmative action in support of its policy and to advance in employment individuals who are minorities, women, protected veterans, and individuals with disabilities.We ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.Please contact us to request accommodation.
Brookhaven Science Associates requires proof of a COVID-19 vaccination for all employees.Proof of full vaccination as recognized by the CDC and/or WHO, inclusive of the two-week waiting period, is required either by November 17, 2021 or at the start of your employment if after November 17, 2021.
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