1 posizione di post-doc in “Urban Boundary Layer Observationalist”
Si segnala una posizione di post-doc in “Urban Boundary Layer Observationalist” presso il CMAS (Center for Multiscale Applied Sensing, USA) . Di seguito maggiori dettagli.
Brookhaven National Laboratory delivers discovery science and transformative technology to power and secure the nation’s future. Brookhaven Lab is a multidisciplinary laboratory with seven Nobel Prize-winning discoveries, 37 R&D 100 Awards, and more than 70 years of pioneering research. The Lab is primarily supported by the U.S. Department of Energy’s (DOE) Office of Science. Brookhaven Science Associates (BSA) operates and manages the Laboratory for DOE. BSA is a partnership between Battelle and The Research Foundation for the State University of New York on behalf of Stony Brook University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country. Our organization fully supports service members transitioning from active duty to civilian life and pledge’s our commitment to actively hire veterans of the U.S. Armed Forces. Military personnel who have been formally trained or have relevant experience obtained while in service may meet educational requirements and are encouraged to apply for job opportunities at BSA.
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 (dispersion, weather extremes, building design) 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 complements work conducted in Brookhaven National Laboratory’s Environmental and Climate Sciences Department.
The Environmental & Climate Sciences Department (www.bnl.gov/envsci) at Brookhaven National Laboratory focuses on a wide range of theoretical, experimental, and field studies in support of the U.S. Department of Energy’s climate and energy research agendas. Work is supported by the Atmospheric Radiation Measurement (ARM) User Facility (www.arm.gov), an observations-based program that measures aerosols, clouds, precipitation, radiation, and atmospheric dynamics; the Atmospheric Systems Research Program; and the Terrestrial Ecosystems Science Program. This work is pursued with the ultimate goal of improving predictability and reducing the uncertainty in global and regional climate models. The department research portfolio also includes development of environmental technologies and applications for renewable energies, urban science, and national security.
The postdoctoral researchers will join the BNL Southwest Urban Integrated Field Laboratory team which will leverage the two mobile observatories developed by BNL’s Center for Multiscale Applied Sensing (CMAS; https://www.bnl.gov/cmas/) to conduct field work in Arizona and conduct data analysis towards
(i) understanding the feedbacks among urban infrastructure, waste heat, and extreme heat/weather events;
(ii) assessing the spatiotemporal patterns of extreme heat and air quality impacts across the diverse urban landscape;
(iii) evaluating the efficacy and social equity of mitigative actions across communities that include traditionally underrepresented groups, and feedbacks and trade-offs between the coupling of greenhouse gas emissions, climate impacts, and air quality.
This position has a high level of interaction with an international and multicultural scientific community.
Essential Duties and Responsibilities:
- Conduct observationally-based research into the urban boundary layer
- Participate in field work to collect observations with the CMAS mobile observatory
- Outline and test deployment strategies for the CMAS mobile observatory for urban boundary layer characterization
- Catalogue/organize field data through the use of a digital database
- Develop new visualization strategies of observation data useful to scientists and stakeholders
- Identify and extract existing datasets relevant to urban climate research through the use of the internet and BNL systems
- Assist urban climate modelers with their assessment of model performance using observations to provide data or compare data to the model output data provided by the modeling team
- Write up and publish results in peer-reviewed journals, in coordination with team leadership
- Assist the principal investigator/researcher with research by reporting on results at regular group meetings and during scheduled seminars and colloquia
- Participate in conferences and workshops, regular group meetings, and note-taking
Required Knowledge, Skills, and Abilities:
- PhD degree in meteorology, atmospheric sciences or a closely related field (e.g., Physics, Engineering)
- Demonstrated experience with analyzing atmospheric or related observational data (e.g., lidar, camera, radar, in-situ)
- Excellent programming skills in various platforms and languages (e.g., Matlab, Python) Ability to work independently and collaboratively
- Clear and concise written and oral communication skills
- Experience writing up and publishing their results in peer-reviewed journals, in coordination with team leadership
- Ability to conduct field work (2-weeks to 1-month US-based campaigns, yearly)
Preferred Knowledge, Skills, and Abilities:
- Experience with analysis of ground-based and spaceborne atmospheric and land surface remote sensing observations (e.g., lidar, radar, infrared and visible imagery)
- Experience with coordinating/planning field deployments based on scientific needs (e.g., siting, route planning)
- Experience with instrument programming (e.g., data logger, scanning sensor)
- Experience with developing multi-dataset or multi-dimensional visualization tools
- Experience with interfacing climate observations and numerical models Experience with analyzing urban form, fabric and function data
- Ability to manage complex, multi-sensor dataset (e.g., through the use of databases, organized server architectures)
- Must be able/willing to travel air and overnight within the U.S. for at least 2-weeks per year
- Valid Driver’s license
- Initial 2-year term appointment subject to renewal contingent on performance and funding
- 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.
- Review of applications begins immediately. Applications will be accepted until the position is filled
- Research is under the direction of Dr. Katia Lamer
At Brookhaven National Laboratory we believe that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. Our benefits program includes, but is not limited to:
- Medical, Dental, and Vision Care Plans
- Flexible Spending Accounts
- Paid Time-off and Leave Programs (vacation, holidays, sick leave, paid parental leave)
- 401(k) Plan Flexible Work Arrangements
- Tuition Assistance, Training and Professional Development Programs
- Employee Fitness/Wellness & Recreation: Gym/Basketball Courts, Weight Room, Fitness Classes, Indoor Pool, Tennis Courts, Sports Clubs/Activities (Basketball, Ping Pong, Softball, Tennis)
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 is required at the start of your employment.
Brookhaven National Laboratory (BNL) is an equal opportunity employer that values inclusion and diversity at our Lab. We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class.
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