Staff Scientist - Extreme Weather, Predictability & AI/ML Forecasting

Staff Scientist - Extreme Weather, Predictability & AI/ML Forecasting We seek a Staff Scientist with expertise in extreme weather and subseasonal-to-decadal predictability, a strong leadership record in climate and atmospheric science, and experience applying AI/ML to forecasting challenges. The ideal candidate is an interdisciplinary researcher who will lead studies of extreme weather in the context of interannual variability and short-term predictability, using AI/ML to improve prediction and interpretation. Berkeley Lab and the University of California system value scientific excellence. You will serve as Laboratory Research Manager (Principal Investigator) for the CASCADE Scientific Focus Area (SFA), a multi-institutional DOE‑funded program focused on understanding and predicting extreme weather across timescales. As LRM, you will lead the SFA’s scientific direction and performance, overseeing meetings, reviews, milestones, budget, personnel, and coordination with DOE program managers. You will work closely with researchers to ensure impactful outcomes, guide program evolution, support dissemination, and foster new initiatives and collaborations within CASCADE and across DOE efforts at LBNL. We’re here for the same mission, to bring science solutions to the world. Join our team and you will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes! We invest in our employees by offering a total rewards package you can count on: Exceptional health and retirement benefits, including pension or 401K‑style plans A culture where you’ll belong - we are invested in our teams! In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year. Parental bonding leave (for both mothers and fathers) You will: Serve as Laboratory Research Manager (PI) for the CASCADE SFA. Apply AI/ML and atmospheric science to advance understanding and near‑term prediction of extreme weather. Identify and pursue interdisciplinary research integrating climate, extremes, human/natural systems, and computational Earth science. Lead and collaborate within large, multidisciplinary teams. Secure funding through proposals as PI/co‑PI and contribute to major collaborative efforts. Mentor and supervise scientists, engineers, and postdocs. Publish research, write reports, and present results at high‑profile venues. Engage in national and international workshops and working groups. We are looking for: Ph.D. degree (or equivalent work experience) in physics, atmospheric science, earth science, or a related field. 10+ years of relevant research experience. Demonstrated excellence in securing external funding as PI and/or co‑PI. Excellent written and oral communication skills. Proven experience leading interdisciplinary collaborative research teams and projects. Experience mentoring and advising early‑career scientists. Serves as an established leader of an independent research program or group, making meaningful contributions to the Division and/or Area in a variety of capacities. Proven track record of independently conceiving, designing, and directing innovative research initiatives with a multi‑year vision with the potential to open new areas of funding. Recognized expert and thought leader within the field, with a well‑established professional reputation. Maintains a sustained record of high‑quality publications in peer‑reviewed, high‑impact journals. Frequently presents research findings at prominent conferences and workshops, and serves as an organizer or in a leadership capacity for such events. Demonstrated success in collaborating with and leading multidisciplinary teams, as well as cultivating and steering intra‑ and inter‑institutional partnerships. Proven ability to contribute effectively as a member of cross‑disciplinary teams and initiatives. Capability to cultivate a community of trust amongst researchers through emotional intelligence. Additional information: Appointment type: This is a full‑time, career appointment, exempt (monthly paid) from overtime pay. Salary range: The expected salary for this position is $173,256 – $242,544, which fits into the full salary of $129,924 – $311,820 depending upon the candidate’s skills, knowledge, and abilities. This includes education, certifications, and years of experience. Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment. Work modality: Work will be primarily performed at: Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here). Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab’s mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law. Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer. #J-18808-Ljbffr Lawrence Berkeley National Laboratory