Brookhaven National Laboratory
Postdoctoral Research Associate – Computational Imaging and Data Science
Brookhaven National Laboratory, Upton, New York, us, 11973
Postdoctoral Research Associate – Computational Imaging and Data Science
Brookhaven National Laboratory is committed to employee success and believes that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. The National Synchrotron Light Source II (NSLS-II) enables its growing research community to study materials with nanoscale resolution and exquisite sensitivity by providing cutting-edge capabilities. Position Description The Coherent Hard X-ray (CHX, 11-ID) beamline at NSLS-II seeks a postdoctoral researcher with a strong background in computational imaging, data science, or scientific computing. This position will focus on developing advanced image reconstruction methods, signal processing techniques, and data analysis pipelines for novel X-ray imaging modalities. As part of a DOE-BER-funded effort to develop a quantum-enhanced X-ray microscope for low-dose biological imaging, the successful candidate will work closely with experimental physicists, biologists, and data scientists. Essential Duties And Responsibilities Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software packages for data processing and simulation. Analyze high-throughput photon event data to extract spatial and temporal correlations. Collaborate with experimental staff on algorithm validation and feedback-driven experiment design. Optimize pipelines for performance, parallelization, and near real-time operation during beam time. Contribute to simulation tools to test imaging concepts, predict performance, and support proposal development. Required Knowledge, Skills, And Abilities Ph.D. in Physics, Computer Science, Applied Mathematics, Engineering, or a related field. Strong programming experience. Knowledge of inverse problems, image reconstruction, or signal processing. Experience with algorithm development for noisy, sparse, or large-scale datasets. Demonstrated ability to work collaboratively with experimentalists and adapt code for real-world data. Preferred Knowledge, Skills, And Abilities Familiarity with compressed sensing and/or convex optimization (e.g., total variation minimization). Expertise in Python, including use of scientific libraries (e.g., NumPy, SciPy, scikit-image, PyTorch/TensorFlow). Experience with deep learning or machine learning approaches to image denoising and reconstruction. Prior exposure to experimental data from photon-counting or time-resolved detectors. Experience with Bayesian methods, uncertainty quantification, or real-time data processing. Familiarity with distributed computing or HPC environments. Equal Opportunity/Affirmative Action Employer Brookhaven Science Associates is an equal opportunity employer that values inclusion and diversity at our Lab. We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class.
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Brookhaven National Laboratory is committed to employee success and believes that a comprehensive employee benefits program is an important and meaningful part of the compensation employees receive. The National Synchrotron Light Source II (NSLS-II) enables its growing research community to study materials with nanoscale resolution and exquisite sensitivity by providing cutting-edge capabilities. Position Description The Coherent Hard X-ray (CHX, 11-ID) beamline at NSLS-II seeks a postdoctoral researcher with a strong background in computational imaging, data science, or scientific computing. This position will focus on developing advanced image reconstruction methods, signal processing techniques, and data analysis pipelines for novel X-ray imaging modalities. As part of a DOE-BER-funded effort to develop a quantum-enhanced X-ray microscope for low-dose biological imaging, the successful candidate will work closely with experimental physicists, biologists, and data scientists. Essential Duties And Responsibilities Develop and implement advanced reconstruction algorithms for correlated and low-dose imaging modalities. Maintain and extend Python-based software packages for data processing and simulation. Analyze high-throughput photon event data to extract spatial and temporal correlations. Collaborate with experimental staff on algorithm validation and feedback-driven experiment design. Optimize pipelines for performance, parallelization, and near real-time operation during beam time. Contribute to simulation tools to test imaging concepts, predict performance, and support proposal development. Required Knowledge, Skills, And Abilities Ph.D. in Physics, Computer Science, Applied Mathematics, Engineering, or a related field. Strong programming experience. Knowledge of inverse problems, image reconstruction, or signal processing. Experience with algorithm development for noisy, sparse, or large-scale datasets. Demonstrated ability to work collaboratively with experimentalists and adapt code for real-world data. Preferred Knowledge, Skills, And Abilities Familiarity with compressed sensing and/or convex optimization (e.g., total variation minimization). Expertise in Python, including use of scientific libraries (e.g., NumPy, SciPy, scikit-image, PyTorch/TensorFlow). Experience with deep learning or machine learning approaches to image denoising and reconstruction. Prior exposure to experimental data from photon-counting or time-resolved detectors. Experience with Bayesian methods, uncertainty quantification, or real-time data processing. Familiarity with distributed computing or HPC environments. Equal Opportunity/Affirmative Action Employer Brookhaven Science Associates is an equal opportunity employer that values inclusion and diversity at our Lab. We are committed to ensuring that all qualified applicants receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, status as a veteran, disability or any other federal, state or local protected class.
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