Computational Postdoctoral Fellow (Optimization and Learning for Imaging)
Lawrence Berkeley National Laboratory | |
United States, California, Berkeley | |
1 Cyclotron Road (Show on map) | |
April 25, 2024 | |
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 from cellular X-ray and 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. 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 May 1, 2024. What You Will Do:
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