Brookhaven National Laboratory’s Center for Multiscale Applied Sensing (CMAS) is a multi-disciplinary center that focuses on providing innovative solutions to challenges influenced by meteorological conditions (contaminant dispersion, weather extremes, building design, renewable energy generation) in highly heterogeneous environments such as cities and complex terrain regions. CMAS does this by innovating on the fronts of meteorological data acquisition, analysis, and interpretation (https://www.bnl.gov/cmas/). The CMAS work portfolio is conducted within Brookhaven National Laboratory’s Environmental and Climate Sciences Department.
The selected candidate will join the BNL’s Center for Multiscale Applied Sensing team primarily as part of the new Southwest Urban Corridor Integrated Field Laboratory team. The Southwest Urban Corridor Integrated Field Laboratory is a multi-institutional project supported by the Department of Energy’s Biological Environmental Research program. The project aims to integrate a diverse suite of high-resolution observations (atmospheric, land surface, and infrastructure), diagnostic/predictive models, and civic engagement to provide new knowledge and deliver next-generation predictive tools. These tools are meant to promote equitable policy interventions targeting extreme climate events, carbon dioxide emissions, and local air pollution within and across the Arizona urban corridor.
The postdoctoral researcher will engage in field work to collect unique weather observations using the CMAS mobile observatory trucks. These observations will then be analyzed by the postdoctoral researcher and the project team to (i) create new understanding of the feedbacks among urban infrastructure, waste heat, and extreme heat/weather events; (ii) assess the spatiotemporal patterns of extreme heat and air quality impacts across the diverse urban landscape; (iii) evaluate the efficacy and social equity of mitigative actions across communities that include traditionally underrepresented groups. This position has a high level of interaction with an international and multicultural scientific community.
Essential Duties and Responsibilities:
- Design field deployment strategies to evaluate and inform next-generation predictive urban climate models (e.g., using OSSEs (Observing System Simulation Experiments) or ablation studies, through extensive literature review of past field campaigns, through interactions with project stakeholders)
- Participate in summer field work
- Conduct observationally based research into the urban boundary layer using “big data” (e.g., crowd sourced data or from mobile and distributed instrument networks)
- Assess the performance of next-generation predictive urban climate models using observations
- Develop new visualization strategies of observational data useful to scientists and stakeholders
- Write and publish results in peer-reviewed journals, in coordination with team leadership
- Report on results at regular group meetings and during scheduled seminars and colloquia
- Participate in conferences and workshops, regular group meetings, and assist with notetaking
Required Knowledge, Skills, and Abilities:
- PhD degree in meteorology, atmospheric sciences, data science, mathematics, or closely related fields (e.g., physics)
- Demonstrated experience with data science, especially statistical hypothesis testing, uncertainty quantification, pattern analysis
- Excellent programming skills in various platforms and languages (e.g., Matlab, Python)
- Ability to work independently and collaboratively
- Clear and concise verbal and written communication and presentation skills
- Must have a valid driver’s license accepted for driving in New York State, or the ability to attain one within 1-month of the date of hire
- Ability to drive a light-duty (“non-CDL”) truck for long durations (up to 8 hours per day)
Preferred Knowledge, Skills, and Abilities:
- Experience with weather instrumentation operation (lidar, radar, weather station, radiometer, sonde, cameras)
- Experience with weather instrumentation data analysis (lidar, radar, weather station, radiometer, sonde, cameras)
- Experience with mining and cleaning “big” observational data and/or online databases
- Experience with interfacing climate observations and numerical models (including the use of instrument forward simulators)
- Experience with developing multi-dataset or multi-dimensional visualization tools
- Experience with analysis of atmospheric numerical model output (e.g., WRF, PALM, SAM)
- Experience with machine learning and artificial intelligence techniques
- Experience with predictive modeling
Environmental, Health & Safety Requirements:
Individual will be required to:
- Wear standard Personnel Protection Equipment
- Climb ladders
- Occasionally work off-hours, nights, or weekends to participate in field work.
- Travel long distances via airplane or otherwise
- Work in inclement weather (heat)
Other Information
- Review of applications begins in April 2025. Applications will be accepted until the position is filled
- Research is under the direction of Dr. Katia Lamer
- Initial 1-year term appointment subject to renewal contingent on performance and funding
- This is a fully onsite position at BNL located in Upton, NY
- BNL policy requires that after obtaining a 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.
- Candidates must have completed all degree requirements by the commencement of the employment.
- Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71900 - $76000 year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group.
