Lawrence Berkeley National Lab’s (LBNL) Physics Division has an opening for a computational Postdoctoral Fellow position in Machine Learning for Particle Physics and Cosmology. 

In this exciting role, you will work with the Physics Division Machine Learning group in developing and deploying methods for optimally combining physics models and simulations with neural networks in order to perform optimal, high-dimensional inference.

The development involves both computational and domain-specific multidisciplinary work, including collaborations with scientists in other LBNL divisions and other institutions. Our current and planned work includes developing normalizing flows to replace Markov Chain Monte Carlo for Uncertainty Quantification, and for high-dimensional integration (for Bayesian evidence and scattering matrix element calculations).  We are also exploring other surrogate models for likelihood-free/simulation-based inference including innovative tools from probabilistic programming.

The posting shall remain open until the position is filled, however for full consideration, please apply by close of business on November 30, 2021.

What You Will Do:

• Work on developing, extending, and implementing surrogate machine learning models to problems in particle physics and cosmology.

• Conduct original research independently and in collaboration.

• Interact with investigators at LBNL and other institutes working on similar or related scientific problems.

• Exercise independent judgment and contribute in an original manner at the professional level.

• Prepare research papers for publication.

• Present research findings at seminars and conferences.

Additional Responsibilities as needed:

• May mentor undergraduate and graduate students.

• Other duties as assigned.

What is Required:

• Ph.D. (or equivalent degree) in physics or related field. 

• Ability to communicate effectively, and to contribute to a large software project.

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

• Relevant publication record and demonstration of proficient written and oral presentation of scientific results.

• A statement describing past activities and future interests in diversity, outreach and leadership (1 page maximum).

Desired Qualifications:

• Experience with machine learning frameworks such as TensorFlow, JAX or PyTorch, high performance computing environments, and any other statistical learning tools and theory.

How To Apply:

For inquiries please contact Kelly Rushing (krushing@lbl.gov). For full consideration, please apply by close of business on November 30, 2021, but the position will remain open until filled.

The following requested application materials listed below must be submitted through Academic Jobs Online:

1. Curriculum vitae.

2. A list of up to ten relevant publications, including contributions for multi-author publications.

3. A statement describing current and future research interests (3-page limit excluding figures and references).

4. A statement describing past activities and future interests in diversity, outreach and leadership (1 page maximum).

5. Arrange to have 3 letters of reference submitted (at least one reference from outside LBNL/UC Berkeley).

Notes:

• This is a full-time, 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.

• This position is represented by a union for collective bargaining purposes.

• Salary will be predetermined based on postdoctoral step rates.

• 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 will be primarily performed at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.