Berkeley Lab
Computational Postdoctoral Fellow (Cryo-EM)
Berkeley Lab, Berkeley, California, United States, 94709
Overview
Berkeley Lab’s (LBNL) Molecular Biophysics and Integrated Bioimaging Division (MBIB) has an opening for a Postdoctoral Fellow to develop computational methods and software for protein structure determination.
In this role, you will develop new mathematical approaches and computational algorithms to investigate protein conformational states from cryo-electron microscopy (Cryo-EM) experiments, including single-particle imaging and cellular tomography. This work will involve research and development of new hybrid methods that combine deep generative modeling, traditional optimization-based methods, numerical linear algebra, and Fourier analysis.
The goals include writing a pipeline for automated atomic modeling of heterogeneous structures from cryo-EM data using Phenix model building tools and developing methods for dealing with incomplete data and structure completion. You will work with a data analysis team for image analysis and the Phenix team for model building aspects. This position will require implementation and testing of software on simulated and experimental data, organization of results for presentations to team members and to the scientific community and preparing results for publication in scientific journals.
This position has an anticipated start date of October 1, 2025.
What You Will Do
Develop and implement computational algorithms for structure determination using cryo-electron microscopy, including generative modeling of conformational heterogeneity in EM data.
Apply data-driven methods that use machine learning for reconstructing non-rigid deformations.
Develop algorithms for automated alignment of single-particle and/or electron tomography data.
Apply theory and optimization techniques to tackle noise, missing data, and completion of models.
Create automated pipelines for data analysis, structure completion, and model validation.
Apply new algorithms to enable high-resolution 3D reconstructions of biomolecules from cellular tomographic data.
Publish scientific papers in high-impact journals and present findings at seminars and conferences.
Maintain documentation of theory, derivations, software, and results.
Contribute to discussions on future directions of the work.
Prepare results, figures, and write-ups for research or grant proposals.
What Is Required
A recent Ph.D. (within the last 1-2 years) in Computational Biophysics/Physics, Computational Cryo-Electron Microscopy, Applied Mathematics, Computer Science, or a related discipline.
Demonstrated experience developing computational algorithms and numerical methods for solving inverse problems in imaging, including iterative reconstruction for microscopy and regularization techniques.
Experience with generative models, variational inference, physics-informed machine learning, and coding in Python and PyTorch.
Demonstrated knowledge of electron microscopy, numerical linear algebra, optimization techniques, and Fourier analysis.
Strong organizational skills including experience maintaining detailed and accurate records of experiment results and analyzed data.
Excellent oral and written communication skills including experience organizing/presenting technical reports and publications in cryo-electron microscopy or closely related fields.
Demonstrated interpersonal skills including the ability to conduct experiments independently and collaborate with a diverse interdisciplinary research team.
Desired Qualifications
Experience coding in C/C++/Fortran and version control tools.
Experience with software development for high-performance computing (e.g., OpenMPI, OpenMP, and GPU).
Interest in extending scientific computing to new imaging problems.
Notes
Application Deadline: For full consideration, apply with a CV or resume and a cover letter describing your interest by September 21, 2025.
Appointment Type: Full-time, exempt from overtime pay, 2-year Postdoctoral Fellow appointment with possible renewal based on performance, funding, and needs. You must have less than 3 years of paid postdoctoral experience. This position is represented by a union for collective bargaining purposes.
Salary Information: Monthly salary range is $7,828 - $8,742, starting at $7,828 or above. Salaries are based on postdoctoral step rates.
Background Check: May be subject to a background check. Convictions will be evaluated for relevance to the position; a history does not automatically disqualify an applicant.
Work Modality: Onsite at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. REAL ID or acceptable ID required to access sites.
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In this role, you will develop new mathematical approaches and computational algorithms to investigate protein conformational states from cryo-electron microscopy (Cryo-EM) experiments, including single-particle imaging and cellular tomography. This work will involve research and development of new hybrid methods that combine deep generative modeling, traditional optimization-based methods, numerical linear algebra, and Fourier analysis.
The goals include writing a pipeline for automated atomic modeling of heterogeneous structures from cryo-EM data using Phenix model building tools and developing methods for dealing with incomplete data and structure completion. You will work with a data analysis team for image analysis and the Phenix team for model building aspects. This position will require implementation and testing of software on simulated and experimental data, organization of results for presentations to team members and to the scientific community and preparing results for publication in scientific journals.
This position has an anticipated start date of October 1, 2025.
What You Will Do
Develop and implement computational algorithms for structure determination using cryo-electron microscopy, including generative modeling of conformational heterogeneity in EM data.
Apply data-driven methods that use machine learning for reconstructing non-rigid deformations.
Develop algorithms for automated alignment of single-particle and/or electron tomography data.
Apply theory and optimization techniques to tackle noise, missing data, and completion of models.
Create automated pipelines for data analysis, structure completion, and model validation.
Apply new algorithms to enable high-resolution 3D reconstructions of biomolecules from cellular tomographic data.
Publish scientific papers in high-impact journals and present findings at seminars and conferences.
Maintain documentation of theory, derivations, software, and results.
Contribute to discussions on future directions of the work.
Prepare results, figures, and write-ups for research or grant proposals.
What Is Required
A recent Ph.D. (within the last 1-2 years) in Computational Biophysics/Physics, Computational Cryo-Electron Microscopy, Applied Mathematics, Computer Science, or a related discipline.
Demonstrated experience developing computational algorithms and numerical methods for solving inverse problems in imaging, including iterative reconstruction for microscopy and regularization techniques.
Experience with generative models, variational inference, physics-informed machine learning, and coding in Python and PyTorch.
Demonstrated knowledge of electron microscopy, numerical linear algebra, optimization techniques, and Fourier analysis.
Strong organizational skills including experience maintaining detailed and accurate records of experiment results and analyzed data.
Excellent oral and written communication skills including experience organizing/presenting technical reports and publications in cryo-electron microscopy or closely related fields.
Demonstrated interpersonal skills including the ability to conduct experiments independently and collaborate with a diverse interdisciplinary research team.
Desired Qualifications
Experience coding in C/C++/Fortran and version control tools.
Experience with software development for high-performance computing (e.g., OpenMPI, OpenMP, and GPU).
Interest in extending scientific computing to new imaging problems.
Notes
Application Deadline: For full consideration, apply with a CV or resume and a cover letter describing your interest by September 21, 2025.
Appointment Type: Full-time, exempt from overtime pay, 2-year Postdoctoral Fellow appointment with possible renewal based on performance, funding, and needs. You must have less than 3 years of paid postdoctoral experience. This position is represented by a union for collective bargaining purposes.
Salary Information: Monthly salary range is $7,828 - $8,742, starting at $7,828 or above. Salaries are based on postdoctoral step rates.
Background Check: May be subject to a background check. Convictions will be evaluated for relevance to the position; a history does not automatically disqualify an applicant.
Work Modality: Onsite at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. REAL ID or acceptable ID required to access sites.
#J-18808-Ljbffr