Computational Postdoctoral Scholar - 93506 Organization: MB-Molecular Biophys & Integ Bio
Lawrence Berkeley National Lab’s (LBNL, https://www.lbl.gov/) Molecular Biophysics and Integrated Bioimaging Division has an opening for a Computational Postdoctoral Researcher to join the team.
In this exciting role, you will work in the Molecular Biophysics and Integrated Bioimaging Division, researching the addition of advanced spatial and symmetry aware neural network training methods to small-molecule chemical crystallography and material science data processing. The data will specifically be from serial crystallographic and micro electron diffraction experiments. The Researcher will build on new approaches in our group that refine crystallographic models to predict signal from X-ray diffraction patterns of small molecules, by applying machine learning principles to learn crystallographic models from the pixel data directly. This will use AI methods developed as part of a close collaboration between teams at Lawrence Berkeley National Labs (LBNL), University of Connecticut, and MIT. The larger group is researching crystal engineering of hybrid coordination polymers towards achieving rational control over the optoelectronic properties of low-dimensional nanostructures. This position is focused on the chemical crystallography aspect of the program, but the successful candidate will be expected to participate in all aspects of the program, including data collection at X-ray free electron lasers worldwide, data analysis on super computing facilities, structure solution, research on AI driven structure prediction, paper writing, and software management. The Postdoctoral appointment is for 3 years.
This work will be part of the Department of Energy Integrated Computational and Data Infrastructure for Science Research program: https://insidehpc.com/2021/08/doe-funds-15m-for-integrated-computational-and-data-infrastructure-for-science-research-at-5-universities/
What You Will Do: • Design and train neural networks to model diffraction from small molecule crystals. This will involve curating training sets from simulated datasets and from existing and new experimental data that will be collected. • Assist in data collection and processing at X-ray free electron sources. • Maintain a detailed record of work performed. • Document and manage code developed using standard source control methods. • Publish in peer-reviewed journals. • Present research at seminars and conferences.
What is Required: • PhD degree in Physics, Statistics, Crystallography, Artificial Intelligence, or a related field. • Experience in computational approaches in at least one of the areas related to the research, including but not limited to small-molecular crystallography, structure solution and refinement, unit cell determination, neural network design, training, and evaluation, high speed computing, image analysis, large dataset analysis, graph theory, error propagation and statistics, signal processing, and GPU acceleration. • Strong analytical and organizational skills. • Excellent interpersonal, oral, and written communication skills. • Ability to work independently as well as part of a diverse team.
Desired Qualifications: • Familiarity with Python, C++, and general scientific data packages such as NumPy, SciPy, and pandas. • Familiarity with small-molecule material design and synthesis.
Notes: • Postdoctoral Scholars - This is a full-time 3 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 2 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree. • 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.
How To Apply Apply directly online at http://50.73.55.13/counter.php?id=206201 and follow the on-line instructions to complete the application process.
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