Algorithm Developer Postdoctoral Fellow
Berkeley Lab's Molecular Biophysics and Integrated Bioimaging Division is looking for a Computational Biologist Postdoctoral Fellow to work in the Sauter group. We are seeking an algorithm developer for the increasingly complex analysis of large diffraction datasets in structural biology. Current projects utilize XFEL crystallography and spectroscopy to investigate the photosynthetic mechanism of water splitting and to probe other metalloenzyme reactions. We also wish to test whether diffuse scattering can reveal correlated atomic motions in crystals. Many problems remain to be solved, including the details of how to optimally merge datasets from thousands of crystals. Our software development projects (including packages such as DIALS and cctbx.xfel) have been highlighted in several high-impact publications listed HERE.
Candidates should have expertise in one or more computational techniques including, but not limited to, ray tracing to test underlying physical models of the diffraction, Bayesian approaches for refining model parameters, macromolecular modeling and refinement, neural networks for interpreting image features, as well as signal processing and denoising methods. Extensive data analysis experience in crystallography or from more general bioimaging backgrounds are welcome. We particularly encourage strong mathematical intuition and a track record of bringing new ideas and tools to fruition, as evidenced through written publication and clear presentation.
Candidates should send an expression of interest, CV, and list of three references to Nick Sauter, nksauter at
lbl.gov. Further details are posted at https://lbl.taleo.net/careersection/2/jobdetail.ftl?lang=en&job=82354.
Bioimaging Project Scientist
A Project Scientist position is open immediately to apply neuromorphic computing techniques to structural biology problems in X-ray diffraction, CryoEM, and CryoET. This will be a cross-disciplinary effort between the Molecular Biophysics and Integrated Bioimaging (MBIB) and Computational Research (CRD) Divisions at Lawrence Berkeley National Laboratory. The successful candidate will investigate how to apply deep learning algorithms to specific data processing and data interpretation problems in structural biology. This will culminate in the implementation of convolutional neural network (CNN) code on neuromorphic computing hardware such as the IBM TrueNorth chip. Example problems include the identification of positive diffraction events in X-ray free-electron laser diffraction, conformational classification in CryoEM single particle reconstruction, and the identification of 3D sections for CryoET subtomogram averaging. To reformulate these structural biology feature extraction problems we will use tools such as MatConvNet, CAFFE, THEANO or TensorFlow to construct and train CNNs that can be used to optimally classify experimental data. The research group will include investigators Nick Sauter (X-ray Crystallography), Karen Davies (CryoEM/ET), and Chao Yang (Scalable Solvers).
Key success factors include experience in Biophysics, Bioinformatics, Mathematics, Computer Science, Engineering or Physical Sciences, preferably a Ph.D. and postdoctoral experience with a strong background in image analysis and machine learning. Knowledge of image classification and neural networks is desired. The successful candidate should be able to program proficiently in MATLAB and/or Python, and should have some knowledge of performance optimization for scientific codes. Excellent verbal and written communication skills are essential, along with a proven ability to identity and formulate research problems.
Candidates should send an expression of interest, CV, and list of three references to Nick Sauter, nksauter at lbl.gov. Further details are posted at https://lbl.taleo.net/careersection/2/jobdetail.ftl?lang=en&job=82354.
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