Research Associate Physics

About this role

Brookhaven National Laboratory (BNL) is entering an exciting new chapter with one of the newest and most advanced synchrotron facilities in the world. National Synchrotron Light Source II (NSLS-II) enables the study of material properties and functions with nanoscale resolution and exquisite sensitivity by providing world-leading capabilities for X-ray imaging and high-resolution energy analysis. This facility is open to users from academia and industry, and its operations are at a time when the world enters a new era with a global economy fueled largely by scientific discoveries and technological innovations. NSLS-II provides the research tools needed to foster new discoveries and create breakthroughs in critical areas such as energy security, environment, and human health.

Position Description The Optics and Metrology Group at NSLS-II seeks a Postdoctoral Research Associate to advance next-generation, non-contact optical fabrication technologies. The successful candidate will contribute to: (1) enhancing removal rate and enabling in-situ beam size and shape control for ion beam figuring (IBF); (2) research & development of Atmospheric Pressure Plasma Jet/Figuring (APPJ/APPF) for efficient figuring and smoothing; and (3) Machine Learning (ML) approaches that improve determinism and predictability across IBF and APPF processes. This position supports an integrated program encompassing advanced control for IBF, APPJ/APPF capability development, hybrid metrology (coordinate measurement, deflectometry, interferometry), and physics-informed ML. The appointee will collaborate closely with internal teams and external plasma experts to innovate damage-free, roughness-preserving fabrication methods and deliver experimentally validated mirror demonstrations.

Essential Duties and Responsibilities: • Einzel-Lens–Enabled IBF • Design, model, integrate and test an Einzel lens and diaphragm module for IBF, enabling real-time tuning of beam current density, spot size, and focal position.

• Develop calibration and diagnostic routines (beam profile, shape, current, stability) and implement closed-loop beam conditioning informed by metrology feedback.

• Atmospheric Pressure Plasma Jet/Figuring (APPJ/APPF) • Develop process recipes (gases, RF/DC power, standoff distance, dwell strategy) that achieve high removal efficiency while preserving surface roughness on Si and SiO₂ substrates.

• Establish plasma and thermal diagnostics (emission, temperature, plume imaging) and integrate in-situ or near-line metrology (e.g., optical coordinate measuring machine) for rapid iteration.

• Develop physics-informed and data-driven models to predict dwell time, raster strategies, and beam/plasma parameters to meet figure and roughness specifications with fewer iterations.

• Apply metrology tools (e.g. interferometry, deflectometry, AFM, SEM) to quantify figure, slope, and roughness, correlating results with process parameters to refine models.

• Publish results in peer-reviewed journal articles and present findings to management and at scientific conferences.

Required Knowledge, Skills, and Abilities: • Ph.D. in Physics, Plasma, Materials, Electrical Engineering, Computer Engineering or related discipline.

• Demonstrated experience in optical surface characterization (e.g., AFM, SEM, coherence-scanning interferometry) and statistical analysis of figure and roughness data.

• Hands-on experience with energy-beam surface processing (e.g. APPJ, IBF, Fluid-jet polishing).

• Strong analytical, experimental design, and problem-solving skills, with effective written and oral communication abilities.

Preferred Knowledge, Skills, and Abilities: • Background in surface, materials science or chemistry (e.g., sputtering and etching mechanisms, plasma-surface interactions, roughness evolution).

• Experience designing, building or operating IBF systems, Einzel lenses, high-voltage or vacuum hardware, gas handling systems, or plasma diagnostics.

• Experience applying ML to process modeling or optimization (e.g., PyTorch, TensorFlow), particularly physics-informed or reinforcement learning approaches.

• Proficiency in control, data acquisition, and instrumentation software (e.g., Python/C++), including experiment automation and data processing.

Other Information: • Occasional travel requirements

• Work arrangement: On-site

• Candidates must have received a Ph.D. by the commencement of employment.  

• BNL policy requires that after obtaining their PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events. 

Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71,900.00 - $88,000.00 / year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group. 

Brookhaven National Laboratory is committed to employee success and we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Review more information at BNL | Benefits Program

Brookhaven National Laboratory requires all non-badged personnel including visitors to produce a REAL-ID or REAL-ID compliant documentation to access Brookhaven National Laboratory – view more information at  www.bnl.gov/real-id .  This is due to nationwide identification requirements for federal site access as required by the federal  REAL ID Act .   Those not in possession of a REAL ID-compliant document will not be permitted to access the site which includes access to the Laboratory for interviews . 

As a U.S. Department of Energy laboratory, Brookhaven National Laboratory requires employees to obtain and maintain a DOE Uncleared P

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