Lawrence Berkeley National Laboratory
Computational Postdoctoral Fellow (Optimization and Learning for Cryo-Electron M
Lawrence Berkeley National Laboratory, Berkeley, California, United States, 94709
Computational Postdoctoral Fellow (Optimization and Learning for Cryo-Electron Microscopy)
Berkeley Lab’s (LBNL) Molecular Biophysics and Integrated Bioimaging Division (MBIB) has an opening for a Postdoctoral Fellow to jointly work with the Applied Mathematics and Computational Research (AMCR) Division and the Center for Advanced Mathematics for Energy Research Applications (CAMERA).In this role, you will develop new mathematical approaches and advanced computational algorithms for multi-conformational imaging including single-particle reconstruction and cellular electron tomography. This work involves research and development in new hybrid methods that couple model-based methods, optimization, numerical linear algebra, Fourier analysis, and deep-learning to solve inverse problems from noisy, incomplete, and heterogeneous data to obtain state-of-the-art reconstructions of protein macromolecules. You will work in a multi-disciplinary team including mathematicians, computational scientists, and biophysicists to implement and test these tools on simulated and experimental data.This position has an anticipated start date of November 1, 2024.What You Will Do:Develop theory and optimization techniques for tackling noise and missing data in cryo-electron tomography for improved sub-tomogram alignment and reconstruction.Develop algorithms for automated marker-less alignment of X-ray and electron tomography data, including rigid-body alignment and non-rigid deformations.Develop new data-driven methods that leverage physics-informed machine learning for handling preferred orientation and for generative modeling of conformational heterogeneity in cryo-electron microscopy.Apply these new algorithms to enable high-resolution 3D reconstructions of biomolecules from single-particle and cellular tomography data.Publish scientific papers in high-impact journals and present findings at seminars and conferences.Maintain documentation of theory, derivations, and results.Prepare results, figures, and write-ups for research/grant proposals.Participate in outreach activities.What is Required:A recent Ph.D. (within the last 1-2 years) in Applied Mathematics, Computational Biophysics/Physics, Computational Biology or a related discipline.Experience with the theory of 3D reconstruction of protein macromolecules from electron microscopy imaging data.Experience with developing numerical methods for solving inverse problems in imaging including but not limited to phase retrieval, iterative reconstruction for tomography, and regularization techniques.Strong background in scientific computing including coding experience in C++, Fortran, and Python.Knowledge of current methods in AI/ML including generative models, variational inference, and physics informed machine learning.Knowledge of numerical linear algebra, optimization techniques, and Fourier analysis.Strong oral and written communication skills including the ability to efficiently organize technical information for publication and presentation.Demonstrated interpersonal skills including experience collaborating with a diverse interdisciplinary research team.Desired Qualifications:Experience with data analysis pipelines for cryo-electron microscopy, such as Relion, cryoSPARC, IMOD.Experience with PyTorch or TensorFlow.Experience with software development for high-performance computing (i.e., openMPI, openMP, and GPU).Experience with version control tools.Interest in extending scientific computing to new imaging problems.Notes:For first consideration, please apply with a curriculum vitae (CV) or resume by October 1, 2024.This is a full time, exempt from overtime pay (monthly paid), 2 year (benefits eligible), Postdoctoral Fellow 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.The monthly salary range for this position is $7,828-$8,742 and is expected to start at $7,828 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries are predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral and/or related research experience.This position is represented by a union for collective bargaining purposes.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 will be performed onsite at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA 94720.Learn About Us:Berkeley Lab (LBNL) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 16 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.Berkeley Lab’s Postdoc Program is committed to providing Postdoctoral Researchers and Visiting scholars with a positive and impactful experience to jump-start their career through premium research and career development, networking opportunities, mentoring programs, and a strong community. For more information, please visit our Berkeley Lab Postdoc Resources site and our Berkeley Lab Postdoc Association site.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.
#J-18808-Ljbffr
Berkeley Lab’s (LBNL) Molecular Biophysics and Integrated Bioimaging Division (MBIB) has an opening for a Postdoctoral Fellow to jointly work with the Applied Mathematics and Computational Research (AMCR) Division and the Center for Advanced Mathematics for Energy Research Applications (CAMERA).In this role, you will develop new mathematical approaches and advanced computational algorithms for multi-conformational imaging including single-particle reconstruction and cellular electron tomography. This work involves research and development in new hybrid methods that couple model-based methods, optimization, numerical linear algebra, Fourier analysis, and deep-learning to solve inverse problems from noisy, incomplete, and heterogeneous data to obtain state-of-the-art reconstructions of protein macromolecules. You will work in a multi-disciplinary team including mathematicians, computational scientists, and biophysicists to implement and test these tools on simulated and experimental data.This position has an anticipated start date of November 1, 2024.What You Will Do:Develop theory and optimization techniques for tackling noise and missing data in cryo-electron tomography for improved sub-tomogram alignment and reconstruction.Develop algorithms for automated marker-less alignment of X-ray and electron tomography data, including rigid-body alignment and non-rigid deformations.Develop new data-driven methods that leverage physics-informed machine learning for handling preferred orientation and for generative modeling of conformational heterogeneity in cryo-electron microscopy.Apply these new algorithms to enable high-resolution 3D reconstructions of biomolecules from single-particle and cellular tomography data.Publish scientific papers in high-impact journals and present findings at seminars and conferences.Maintain documentation of theory, derivations, and results.Prepare results, figures, and write-ups for research/grant proposals.Participate in outreach activities.What is Required:A recent Ph.D. (within the last 1-2 years) in Applied Mathematics, Computational Biophysics/Physics, Computational Biology or a related discipline.Experience with the theory of 3D reconstruction of protein macromolecules from electron microscopy imaging data.Experience with developing numerical methods for solving inverse problems in imaging including but not limited to phase retrieval, iterative reconstruction for tomography, and regularization techniques.Strong background in scientific computing including coding experience in C++, Fortran, and Python.Knowledge of current methods in AI/ML including generative models, variational inference, and physics informed machine learning.Knowledge of numerical linear algebra, optimization techniques, and Fourier analysis.Strong oral and written communication skills including the ability to efficiently organize technical information for publication and presentation.Demonstrated interpersonal skills including experience collaborating with a diverse interdisciplinary research team.Desired Qualifications:Experience with data analysis pipelines for cryo-electron microscopy, such as Relion, cryoSPARC, IMOD.Experience with PyTorch or TensorFlow.Experience with software development for high-performance computing (i.e., openMPI, openMP, and GPU).Experience with version control tools.Interest in extending scientific computing to new imaging problems.Notes:For first consideration, please apply with a curriculum vitae (CV) or resume by October 1, 2024.This is a full time, exempt from overtime pay (monthly paid), 2 year (benefits eligible), Postdoctoral Fellow 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.The monthly salary range for this position is $7,828-$8,742 and is expected to start at $7,828 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries are predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral and/or related research experience.This position is represented by a union for collective bargaining purposes.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 will be performed onsite at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA 94720.Learn About Us:Berkeley Lab (LBNL) addresses the world’s most urgent scientific challenges by advancing sustainable energy, protecting human health, creating new materials, and revealing the origin and fate of the universe. Founded in 1931, Berkeley Lab’s scientific expertise has been recognized with 16 Nobel prizes. The University of California manages Berkeley Lab for the U.S. Department of Energy’s Office of Science.Berkeley Lab’s Postdoc Program is committed to providing Postdoctoral Researchers and Visiting scholars with a positive and impactful experience to jump-start their career through premium research and career development, networking opportunities, mentoring programs, and a strong community. For more information, please visit our Berkeley Lab Postdoc Resources site and our Berkeley Lab Postdoc Association site.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.
#J-18808-Ljbffr