Larson and Hope Labs - Junior/Assistant/Associate/Full Specialist

University of California San Francisco

$57K — $201K *
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Baccalaureate degree in computer science or related field with 4 years of research experience for Junior rank.
  • Master's degree or Bachelor's with 3+ years of research experience for Assistant rank.
  • Master's degree or 5-10 years of research experience for Associate rank.
  • Terminal degree or 10+ years of research experience for Full rank.
  • Current/pending qualifications required upon application submission.

Responsibilities

  • Develop and validate deep learning models for medical image segmentation.
  • Design and implement pipelines integrating LLMs with image-based analysis algorithms.
  • Curate and manage large-scale cancer imaging datasets in collaboration with partners.
  • Disseminate research findings through peer-reviewed publications.
  • Contribute to grant applications and collaborative projects across various settings.

Benefits

  • Exposure to translational and commercial development pipelines through collaborations.
  • Opportunities for publishing in high-impact journals.
  • Access to cutting-edge technology and methods in AI for cancer imaging.
  • Potential for interdisciplinary collaboration with industry partners.
  • Working in a leading environment for clinical translation of innovative imaging technologies.
Full Job Description
Application Window

Open date: July 22, 2026

Next review date: Thursday, Aug 6, 2026 at 11:59pm (Pacific Time) Apply by this date to ensure full consideration by the committee.

Final date: Saturday, Jan 22, 2028 at 11:59pm (Pacific Time) Applications will continue to be accepted until this date, but those received after the review date will only be considered if the position has not yet been filled.

Position description

Larson and Hope Labs - Junior/Assistant/Associate/Full Specialist

The Larson and Hope Labs are seeking a Junior, Assistant, Associate, or Full Specialist. This position focuses on the development and application of cutting-edge artificial intelligence methods for automated analysis of cancer imaging data, with an emphasis on integrating large language models (LLMs) with image-based segmentation and interpretation algorithms. A primary application will be segmentation and quantitative analysis of PSMA PET imaging in prostate cancer, with additional projects spanning radiology-based AI applications across modalities.

UCSF has led the clinical translation of PSMA PET imaging, and this position represents a key next step in developing advanced computational tools to maximize its clinical and research utility. The successful candidate will also benefit from active collaborations with multiple industry partners, providing exposure to translational and commercial development pipelines.

Responsibilities include:

  • Developing and validating deep learning models for medical image segmentation, with a focus on PSMA PET and broader radiology applications
  • Designing and implementing pipelines that integrate LLMs with image-based analysis algorithms for enhanced interpretation and reporting
  • Curating and managing large-scale cancer imaging datasets in collaboration with clinical and industry partners
  • Disseminating research findings through peer-reviewed publications, with target venues including Radiology: Artificial Intelligence, Journal of Nuclear Medicine, and IEEE Transactions on Medical Imaging and related IEEE journals
  • Contributing to grant applications and collaborative research projects across academic and industry settings

Required Qualifications:

  • Specialists appointed at the Junior rank must possess a baccalaureate degree (or equivalent degree) in computer science, electrical engineering, biomedical engineering, data science, or a closely related field, or at least four years of research experience.
  • Specialists appointed at the Assistant rank must possess a master's degree (or equivalent degree) or a baccalaureate degree (or equivalent degree) with three or more years of research experience.
  • Specialists appointed at the Associate rank must possess a master's degree (or equivalent degree) or five to ten years of research experience.
  • Specialists appointed at the Full rank must possess a terminal degree (or equivalent degree) or ten or more years of research experience.
  • Applicants must meet all the qualifications by the time of hire.
  • Applicant materials must list current and/or pending qualifications upon submission.

Preferred Qualifications:

  • Scientific Computing programming experience (e.g. MATLAB, Python)
  • Experience working with imaging datasets and image processing
  • Experience with high-performance computing environments, including Linux/Unix, and running algorithms on CPUs and GPUs
  • Deep learning frameworks, particularly Python and PyTorch
  • Medical image segmentation and computer vision model development
  • Large language models and multimodal AI architectures
  • Setting up and managing large imaging datasets
  • Strong written communication skills and a track record of, or clear enthusiasm for, first-author publication are essential
  • PhD in computer science, electrical engineering, biomedical engineering, data science, or a closely related field is strongly preferred

See Table 24B for the salary range for this position. A reasonable estimate for this position is $57,000-$201,700.

Please click here to apply with cover letter, CV, and contact information for three references.

Application Requirements

Document requirements
  • Cover Letter
  • Curriculum Vitae - CV must clearly list current and/or pending qualifications (e.g. board eligibility/certification, medical licensure, etc.).
  • Statement of Research (Optional)


Reference requirements
  • 3 required (contact information only)


Job location

San Francisco, CA

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