Machine Learning Postdoctoral Fellow
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Lawrence Berkeley National Laboratory
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Berkeley, CA 94720
SessionJob Postings
DescriptionComputational Scientist Project Scientist - 97210
Division: DD-Data Science
Lawrence Berkeley National Lab’s (LBNL, https://www.lbl.gov/) Data Science Division has an opening for a Computational Scientist Project Scientist to join the team.
In this exciting role, you will work on the development of scientific machine learning models, with an emphasis on the intersection of deep learning, dynamical systems, and robustness, in order to address questions such as how to build robust dynamical systems that are computational efficient and expressive for scientific and engineering machine learning problems. Among other things, this will involve leveraging tools from randomized numerical linear algebra to build algorithms for data-intensive applications such as fluid flows and climate science.
What You Will Do:
• Lead the design, development, and optimizations of machine learning algorithms for dynamical systems problems.
• Develop self-supervised and transfer learning methods for super-resolution tasks and data problems.
• Integrate these methods into ODE/PDE-based SciML pipelines.
• Development of robust and dynamical systems inspired neural network architectures, efficient training strategies for extracting knowledge from limited data, and data-driven modeling of scientific data.
• Develop and evaluate randomized implementations so they work efficiently with dense matrices, sparse matrices, and even abstract linear operators.
• Work closely with NERSC scientists and Machine Learning and Analytics scientists to deploy and evaluate the implementations of novel algorithms, including evaluation on fluid, climate, astronomy, etc., data.
• Provide training to colleagues and write excellent documentation, to elevate the work from a proof of concept to maintainable, long-lasting infrastructure.
Additional Responsibilities as needed:
• Experience in numerical analysis, statistics, machine learning, and numerical optimization.
• Experience in one or more application areas such as fluid flow, climate science, etc.
• Experience in machine learning development, including training and evaluation of neural network models.
• Experience creating, implementing, and applying data analysis methods and procedures.
Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs?
Please visit: https://recruiting.lbl.gov/
Notes:
• This is a full time, 2 year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
• 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.
• Work may be performed on-site, hybrid, full-time telework. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
How To Apply
Apply directly online at http://50.73.55.13/counter.php?id=243107 and follow the on-line instructions to complete the application process.
Based on University of California Policy - SARS-CoV-2 (COVID-19) Vaccination Program and U.S Federal Government requirements, Berkeley Lab requires that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of employment at Berkeley Lab, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof of Full Vaccination or submitting a request for Exception or Deferral. Visit covid.lbl.gov (https://covid.lbl.gov/) for more information.
Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA, https://diversity.lbl.gov/ideaberkeleylab/) 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 (https://www.dol.gov/agencies/ofccp/posters) for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision (https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf) under 41 CFR 60-1.4.
Division: DD-Data Science
Lawrence Berkeley National Lab’s (LBNL, https://www.lbl.gov/) Data Science Division has an opening for a Computational Scientist Project Scientist to join the team.
In this exciting role, you will work on the development of scientific machine learning models, with an emphasis on the intersection of deep learning, dynamical systems, and robustness, in order to address questions such as how to build robust dynamical systems that are computational efficient and expressive for scientific and engineering machine learning problems. Among other things, this will involve leveraging tools from randomized numerical linear algebra to build algorithms for data-intensive applications such as fluid flows and climate science.
What You Will Do:
• Lead the design, development, and optimizations of machine learning algorithms for dynamical systems problems.
• Develop self-supervised and transfer learning methods for super-resolution tasks and data problems.
• Integrate these methods into ODE/PDE-based SciML pipelines.
• Development of robust and dynamical systems inspired neural network architectures, efficient training strategies for extracting knowledge from limited data, and data-driven modeling of scientific data.
• Develop and evaluate randomized implementations so they work efficiently with dense matrices, sparse matrices, and even abstract linear operators.
• Work closely with NERSC scientists and Machine Learning and Analytics scientists to deploy and evaluate the implementations of novel algorithms, including evaluation on fluid, climate, astronomy, etc., data.
• Provide training to colleagues and write excellent documentation, to elevate the work from a proof of concept to maintainable, long-lasting infrastructure.
Additional Responsibilities as needed:
• Experience in numerical analysis, statistics, machine learning, and numerical optimization.
• Experience in one or more application areas such as fluid flow, climate science, etc.
• Experience in machine learning development, including training and evaluation of neural network models.
• Experience creating, implementing, and applying data analysis methods and procedures.
Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs?
Please visit: https://recruiting.lbl.gov/
Notes:
• This is a full time, 2 year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
• 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.
• Work may be performed on-site, hybrid, full-time telework. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
How To Apply
Apply directly online at http://50.73.55.13/counter.php?id=243107 and follow the on-line instructions to complete the application process.
Based on University of California Policy - SARS-CoV-2 (COVID-19) Vaccination Program and U.S Federal Government requirements, Berkeley Lab requires that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of employment at Berkeley Lab, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof of Full Vaccination or submitting a request for Exception or Deferral. Visit covid.lbl.gov (https://covid.lbl.gov/) for more information.
Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA, https://diversity.lbl.gov/ideaberkeleylab/) 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 (https://www.dol.gov/agencies/ofccp/posters) for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision (https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf) under 41 CFR 60-1.4.
RequirementsWhat is Required:
• PhD in Computer Science or Applied Mathematics, or a related field or equivalent combination of skills and experience.
• Significant experience in developing novel scientific machine learning methods.
• Experience in developing new numerical algorithms for optimization, linear algebra, data analysis, statistical models.
• Demonstrated record of scientific excellence through publications, talks, talks, or software deliverables.
• Ability to work collaboratively with a diverse team of scientists and engineers.
• Demonstrated expertise at successfully working in multidisciplinary teams. In particular, demonstrated expertise in coordinating machine learning teams.
• Ability to interact with a variety of technical and scientific personnel including Research Associates, Scientists and Software Engineers with varied academic backgrounds.
• Strong written and verbal communication skills to present and disseminate scientific software developments at group meetings and conferences.
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·
2022-10-28
Event Type
Job Posting
TimeWednesday, 16 November 202210am - 3pm CST
Location