HOWARD HUGHES MEDICAL INSTITUTE HHMI

HOWARD HUGHES MEDICAL INSTITUTE HHMI

AI Engineer - AI+CryoET

Janelia Research Campus, USA · Principal

Sponsorship not specified$96k-$120kDetected 65 days ago
PythonGitLinuxMachine LearningDeep LearningPyTorchHRISStructural AnalysisMicroscopyExperimental DesignCommunicationCollaboration

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53Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level II)66
Fits your clock70

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About the role

  • This role is part of the AI+CryoET project within AI@HHMI, a multi-institutional project at the intersection of cryo-electron tomography (cryoET), molecular dynamics simulation, and machine learning.
  • (2) identifying the arrangement and connectivity of nucleosomes in chromatin that give rise to chromosome structure in cell nuclei and biochemical reconstitutions.
  • Success in this role requires close collaboration with cryoET experts, structural biologists, and computer scientists to ensure models work in challenging real-world scenarios of a biologically not yet fully understood system.

Responsibilities

  • 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.
  • AI@HHMI: HHMI is investing $500 million over the next 10 years to support AI-driven projects and to embed AI systems throughout every stage of the scientific process in labs across HHMI.
  • The project aims to develop AI methods for mesoscale structural biology, understanding how cellular macromolecules organize into higher-order structures.
  • Opportunity to partner with frontier AI labs on scientific applications of AI.

Requirements

  • The position requires mobility, including the ability to move materials weighing up to several pounds (such as a laptop computer or tablet).
  • ability to see and hear within normal parameters
  • ability to move about workspace.
  • Strong Python skills, and proficiency in PyTorch and/or JAX.
  • 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.
  • Ways to stand out:
  • 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.

Nice to have

  • Current HHMI Employees, click here to apply via your Workday account.
  • Please include a cover letter with your application.
  • Cryo-EM/ET and computational structural biology projects are especially relevant.
  • Discuss results, limitations, and challenges encountered.
  • If the project was collaborative, describe your specific contributions.
  • Include links to relevant code repositories and your GitHub/Gitlab profile, personal website, or similar evidence.
  • Experience with detection, segmentation, or inverse problems in imaging is strongly preferred.

Compensation

  • Our employees are compensated from a total rewards perspective in many ways for their contributions to our mission, including competitive pay, exceptional health benefits, retirement plans, time off, and a range of recognition and wellness programs.
  • The posted range reflects HHMI's good faith estimate of the anticipated hiring salary range for this role at the time of posting.
  • Actual hiring compensation is determined by a candidate's qualifications, experience, and internal equity.
  • Compensation and Benefits

Benefits

  • A competitive compensation package with comprehensive health and welfare benefits.
  • See https://www.anthropic.com/news/anthropic-partners-with-allen-institute-and-howard-hughes-medical-institute
  • 3+ years training and evaluating deep learning models, particularly on 3D or volumetric image data.
  • Visit our Benefits at HHMI site to learn more.

Equal opportunity

  • HHMI is an Equal Opportunity Employer
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