Lawrence Berkeley National Lab's (LBNL) National Energy Research Scientific Computing Center (NERSC) is inviting applications for the position of Data Department Head (AI, Science Engagement, and Storage)
NERSC's mission is to accelerate scientific discovery through high performance computing, data analysis and AI for the DOE Office of Science programs. NERSC provides critical HPC and data systems and support for NERSC's 9000+ users researching alternative energy sources, climate science, energy efficiency, environmental science and other DOE mission areas. Data intensive computing is becoming a larger fraction of the NERSC workload as DOE Experimental and Observational Facilities increasingly transfer data to NERSC to analyze. NERSC is seeking an inspired leader for the Data Department who will provide vision and guidance for a department that includes the following groups: Data and AI Services, Data Science Engagement and Storage Systems.
The department of approximately 40 technical staff members and postdocs is responsible for supporting a range of data processing and AI software, engaging with experimental and observational science, as well as deploying and operating community and HPSS storage systems. The Data Department Head is a member of the management team that sets strategic directions and prioritizes work across NERSC, and works closely with colleagues in the national laboratories, leading research universities, Department of Energy and HPC communities. What You Will Do:
What is Required:
- Serve as a key member of NERSC's leadership team to set strategic directions for NERSC and influence the direction of the HPC community on a large-scale, nationwide basis.
- Provide vision and strategic direction for the Data Department.
- Communicate with stakeholders within the Department of Energy Office of Science.
- Assure NERSC's HPC and data systems are high performing and productive platforms for NERSC users.
- Provide effective line management for the department by hiring excellent staff and conducting performance management. Assure staff are meeting goals and provide both positive and constructive feedback to staff and keep them motivated.
- Play a key leadership role in designing and deploying advanced technology supercomputers, data systems and workflow software.
- Oversee preparation for DOE and UC-sponsored program reviews, and act as a peer reviewer for other organizations.
- Work closely with other teams and departments at NERSC to enable large-scale data intensive applications to run seamlessly across NERSC's supercomputing and data systems.
- Maintain a work environment that embraces diversity and fosters creativity and innovation.
- Ensure that DOE and Laboratory rules and policies are observed.
- Bachelor's degree (or equivalent related experience) in Computer Science, Applied Mathematics, Computational Science (or related fields) and a minimum of 12 years related experience and 5 years in a supervisory role.
- Nationally recognized expertise in one or more of the following areas: HPC systems and applications, data intensive computing, AI and/or storage.
- Experience running applications on, or deploying large-scale HPC and data systems.
- Demonstrated experience/proven track record managing large organizations and/or complex projects.
- Demonstrated ability to run a moderate-sized, team-oriented organization and attract, retain and develop a talented and diverse staff, foster positive work relationships and to resolve technical and interpersonal conflicts with diplomacy and tact.
- Demonstrated ability to lead a team-oriented organization and attract, retain and develop a talented and diverse staff.
- Ability to foster positive work relationships and resolve technical and personal conflicts with diplomacy and tact.
- Ability to gather requirements from the user community and turn requirements into system and software characteristics.
- Ability to travel to meetings, workshops and conferences.
- Excellent written and interpersonal communication skills; demonstrated high level of collaboration skills with technical peers, vendors, and NERSC users.
The full salary range of this position is between $15,725 to $26,535 per month and is expected to pay between a targeted range of $17,690 to $21,621 per month depending upon the candidate's full skills, knowledge, and abilities, including education, certifications, and years of experience. Notes:
- This is a full-time career appointment, exempt (monthly paid) from overtime pay.
- This position will be hired at a level commensurate with the business needs and the skills, knowledge, and abilities of the successful candidate.
- This position may be 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.
- This position is eligible for a hybrid work schedule - a combination of teleworking and performing work on site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work schedules are dependent on business needs. Individuals working a hybrid schedule must reside within 150 miles of Berkeley Lab.
Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA) and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab's mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse 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, or protected veteran status.
Equal Opportunity and IDEA Information Links: Know your rights, click here for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision under 41 CFR 60-1.4.