Reconstruction Experts Jobs in Virginia (NOW HIRING)

Job Summary:
Howard Hughes Medical Institute (HHMI) is investing significantly to support AI-driven projects in scientific research. The AI Engineer role involves developing AI methods for 3D particle detection and structural analysis in cryo-electron tomography data, collaborating closely with experts across multiple institutions.
Responsibilities:
• Develop and evaluate deep learning models for detecting and localizing gold nanoparticles and macromolecular particles (e.g., nucleosomes, synaptic receptors) in cryoET data, and for identification of nucleosome arrangement and connectivity in chromatin.
• Develop methods to leverage gold nanoparticle detections to improve tomogram reconstruction, addressing challenges in tilt-series alignment, deformations, and low signal-to-noise conditions.
• Design and execute rigorous AI model training and evaluation pipelines, including proper handling of missing wedge artifacts, CTF effects, and sim-to-real transfer from MD-derived synthetic training data.
• Identify where additional human annotation and proofreading will be most helpful and design and guide annotation efforts.
• Contribute to scientific publications, present findings at conferences, and maintain a well-documented codebase enabling seamless reproduction and extension of results.
• Collaborate with interdisciplinary teams across multiple institutions.
Qualifications:
Required:
• Master's or PhD in Computer Science, Applied Mathematics, Physics, Computational Chemistry, or a related field, or equivalent combination of education and experience.
• 3+ years training and evaluating deep learning models, particularly on 3D or volumetric image data. Experience with detection, segmentation, or inverse problems in imaging is strongly preferred.
• Strong Python skills, and proficiency in PyTorch and/or JAX. Ability to reason about neural network behavior from first principles: how architectural choices, regularization, and training procedures affect model behavior.
• Rigorous experimental design: model comparisons, ablation studies, reproducibility.
• Commitment to open science.
• Experience with scalable GPU-based computing environments on Linux HPC clusters and high-throughput processing for large-scale data.
• Excellent communication skills and keen interest in working in a truly interdisciplinary environment.
Preferred:
• Experience with cryo-EM/ET data processing, tomographic reconstruction, or related inverse problems in imaging.
• Familiarity with molecular dynamics simulations (e.g., OpenMM, LAMMPS) and/or synthetic data generation for training ML models.
• Experience with differentiable rendering, neural radiance fields, or analysis-by-synthesis approaches for 3D reconstruction.
• Knowledge of cryoET software tools (IMOD, Warp, RELION, AreTomo etc.) or microscopy data formats (MRC, Zarr).
• Experience with template matching, sub-tomogram averaging, or particle picking in cryo-EM/ET contexts.
Company:
Founded in 1953, HHMI invests in scientists at all career stages who make discoveries that advance human health and our fundamental understanding of biology. Founded in 1953, the company is headquartered in Chevy Chase, USA, with a team of 1001-5000 employees. The company is currently Late Stage.