Machine Learning Postdoctoral Fellow

Berkeley, Ca

Applications have closed

Lawrence Berkeley National Lab

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Machine Learning Postdoctoral Fellow - 100554

Division: NE-NERSC

 

The National Energy Research Scientific Computing Center (NERSC) and Physics Division at Berkeley Lab are seeking a highly motivated Machine Learning Postdoctoral Fellow to join a novel project on systematic-aware AI benchmarking for High-Energy Physics (HEP). 

 

We are building a supercomputer-scale AI ecosystem for sharing datasets, training large models, and hosting machine-learning challenges and benchmarks. This ecosystem will be initially exploited for a ML challenge series,  based on novel datasets and progressively rolling in tasks of increasing difficulty focusing on discovering and minimizing the effects of systematic uncertainties in HEP.

 

In this exciting role, you will work with a multidisciplinary team including machine learning researchers and physicists to build AI challenges, models and software that exploit supercomputers at NERSC. 

 

NERSC and the LBL Physics division have established track records of enabling their postdocs to pursue careers in physics, machine learning and scientific computing in industry, national labs and academia.

 

What You Will Do:

• Create datasets, tasks, metrics and models to push the development of systematic-uncertainty aware AI techniques in particle physics and cosmology.

• Contribute to the running of AI challenges and the creation of long-lived benchmarks addressing compelling questions about the impact of systematic effects in AI models.

• Help develop an AI benchmark platform, interfaced to supercomputers at NERSC and capable of hosting datasets and models; producing new simulated datasets; applying new AI algorithms on existing datasets; and applying uploaded AI algorithms on new datasets.

• Disseminate results of research activities through refereed publications, reports, and conference presentations. 

• Participation in postdoctoral career and science enrichment activities within the Berkeley Lab Computing Sciences Area is encouraged.

 

What is Required:

• Ph.D. in Physics, Computer Science, Applied Mathematics, or another numerical science domain area.

• Demonstrably effective communication and interpersonal skills.

• Demonstrated ability to perform research individually and as part of a research group.

• Ability to contribute to a large software project.

• Ability to work productively both independently and as part of an interdisciplinary team, balancing objectives involving research and code development.

 

Desired Qualifications:

• Publication record and/or contributions to open source software projects commensurate with years of experience.

• Experience with machine learning/deep learning frameworks such as TensorFlow, PyTorch, scikit-learn.

• Experience in building and training ML/DL models.

 

For full consideration, please apply by January 5, 2024.

 

Want to learn more about Berkeley Lab's Culture, Benefits and answers to FAQs? Please visit: https://recruiting.lbl.gov/

 

Notes:

• This position requires substantial on-site presence, but is eligible for a flexible work mode, and hybrid schedules may be considered. Hybrid work is a combination of performing work on-site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA and some telework. Individuals working a hybrid schedule must reside within 150 miles of Berkeley Lab. Work schedules are dependent on business needs. In rare cases, full-time telework or remote work modes may be considered.

• The monthly salary range for this position is $6431-$10114 and is expected to start at $8078 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral experience.

• 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.

 

How To Apply

Apply directly online at http://50.73.55.13/counter.php?id=273361 and follow the on-line instructions to complete the application process.

 

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.

Tags: Computer Science Deep Learning Machine Learning Mathematics Open Source PHP Physics PyTorch Research Scikit-learn TensorFlow

Perks/benefits: Career development Equity Flex hours Team events

Region: North America
Country: United States

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