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Assistant/Associate/Full Researcher - Machine Learning Models - Advanced Bioimaging Center - Department of Molecular and Cell Biology

University of California-Berkeley
United States, California, Berkeley
Feb 26, 2026
Position overview
Position title:
Assistant/Associate/Full Researcher
Salary range:
The UC academic salary scales set the minimum pay determined by rank and step at appointment. See the following table for the current salary scale for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/policy-covered-july-2025-scales/t13-a.pdf. A reasonable estimate for this position is $199,700- $357,200.
Percent time:
100%
Anticipated start:
Winter/Spring 2026
Position duration:
Initial appointment is for one year with the possibility of renewal based on performance and funding availability.


Application Window


Open date: February 26, 2026




Next review date: Thursday, Mar 12, 2026 at 11:59pm (Pacific Time)

Apply by this date to ensure full consideration by the committee.




Final date: Saturday, Mar 28, 2026 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

The Advanced BioImaging Center (ABC) in the Department of Molecular and Cell Biology at the University of California, Berkeley seeks applications for a Professional Researcher at the Assistant, Associate, or Full rank. The selected candidate will be appointed at the rank to commensurate with prior experience. The position will report to Professor Gokul Upadhyayula, with Professor Eric Betzig serving as an additional academic mentor. The researcher will conduct independent research at a level comparable to the Professor series.

The Advanced BioImaging Center (ABC) at UC Berkeley aspires to be a world-leading multidisciplinary imaging center that drives important biological discoveries through critical new advances in all aspects of imaging technology and that drives the dissemination of that technology through a multi-pronged education strategy to scientists around the world. ABC was intentionally designed to maximize scientific productivity and impact by adopting groundbreaking imaging technologies such as the next-generation adaptive optical multifunctional microscope, incorporating the high-level technical expertise of instrumentation scientists, applied mathematicians, and computational scientists, and building worldwide collaborations aimed at tackling the challenges posed by terabyte and petabyte-scale imaging data processing, visualization, and dissemination. Members of the ABC have access to leading - edge imaging and computing hardware, as well as exposure to collaborators from a range of diverse disciplines, including in the fields of Artificial Intelligence, Data Science, Mathematics, and more.

This position will focus on advanced, independent research leading the ABC computational team to develop vision-transformer-based foundation machine learning models. The Researcher will work closely with an interdisciplinary team of optical physicists, engineers, and computational imaging researchers to achieve the ambitious goal of creating a generative AI model for segmenting and querying complex 4D high-resolution data of zebrafish development. This is an exciting opportunity to contribute to advancing biological imaging and AI-driven data analysis at the intersection of biology and computational science.

As this project grows, the individual will be expected to expand their leadership and adapt to the evolving scope of the research. The role will begin with leading efforts to supervise data collection and management, model development, and collaborating with leadership across the center. The researcher will build and manage a team of data scientists, and computational biologists to test AI-driven imaging models and will facilitate scientific collaborations with local, domestic, and international researchers. This position will take on a growing role and contribute to a groundbreaking initiative in biological imaging.

Key Responsibilities:

*Conduct and design independent research and lead a team of data scientists and software engineers to enable the development of state-of-the-art AI models for light sheet microscopy data.

*Collaborate with experts in optical physics, engineering, and computational imaging to support a foundational AI model for high-resolution developmental biology data.

*Conduct and lead experimental design, data acquisition, and data analysis pipelines to ensure optimal data quality.

*Facilitate and maintain scientific collaborations with local, domestic, and international researchers as the project expands.

*Publish research findings in high-impact journals and presenting at scientific conferences.

*Supervise and mentor graduate students, postdoctoral fellows, staff scientists, and academic research titles involved in machine learning and biological data analysis.

*Lead the development of new AI models and data processing tools for datasets generated on multicellular tissues, organoids, transparent embryos.

*Oversee the design and development of new machine learning tools for petabyte-scale light sheet datasets that are typically 4D or 5D (x,y,z,t,chemistry).

*Advise on applications of these tools for biological imaging; collaborate with graduate students, postdoctoral fellows and academic research titles on specific projects to test, learn and implement for general and specific use cases.

*Bring cross disciplinary expertise to solve problems at the intersection between life science, computer vision, and state-of-the-art AI methods.

*Identify and study scaling laws for machine learning models on large-scale 5D light sheet datasets.

*Organize and plan on the design and development of new AI techniques to further ABC's mission.

Lab: https://abc.berkeley.edu/


Qualifications
Basic qualifications (required at time of application)

PhD (or equivalent international degree)

Additional qualifications (required at time of start)

Two (2) years of post PhD research experience.

For consideration for Associate Researcher rank, a minimum of 8 years of post PhD research experience as a group leader or principal investigator (PI) supervising a team of PhD-level scientists in industry or academia.

For consideration for full Researcher rank, a minimum of 14 years post PhD research experience, including a minimum of 8 years of experience leading a team as a principal investigator (PI) at the university level or in industry with demonstrated success managing graduate students, postdoctoral researchers, technicians, or equivalent positions.

Preferred qualifications

*PhD or equivalent international degree in Data Science, Computer Science, Bioinformatics or Related field.

*Hands-on experience with developing machine learning models for large-scale light sheet microscopy.

*Strong publication record indicating research independence and leadership.

*Excellent communication, organizational, and leadership skills.

*Proven track record of interdisciplinary collaboration, especially in integrating machine learning with biological research, physics, engineering, or computational fields.

*Demonstrated experience working with large-scale biological datasets, including experience with computational image analysis.

*Demonstrate understanding of optical microscopy, including light sheet microscopy, adaptive optics, and modern scientific cameras.

*Demonstrated ability to work in a research team, manage active collaborations with other academic groups.

*Demonstrated experience handling and processing large scale imaging datasets (>100TB to petabyte scale and beyond).

*Expertise in programming in C/C++, MATLAB, Bash.

*Expertise in databases, data infrastructure, data governance.

*Expertise in high performance computing using SLURM or LSF.

*Experience with PyTorch, JAX, or Tensorflow.

*Experience with NVIDIA CUDA and related OpenMP programming.

*Experience with cloud services (AWS, GCP, Azure, etc.).

*Experience with state of the art AI/ML architectures (vison transformers, diffusion models, etc.).

*Experience supervising and mentoring undergraduate/graduate students, and/or technicians.

*Ability to effectively communicate, participate in efficient and open collaboration, and engage with a diverse group of researchers.

*The ideal candidate will be innovative and able to synergize various ideas and approaches, while exercising sound judgment to evaluate and take acceptable risks.

*Expertise in leading teams in executing machine learning projects, as evidenced by last author peer-reviewed publications within their scientific discipline.

*Readiness to scale efforts and grow with the expanding scope of the project, including building and managing a team and facilitating collaborations.


Application Requirements
Document requirements
  • Curriculum Vitae - Your most recently updated C.V.


  • Cover Letter


  • Research Statement - Please discuss research accomplishments and proposed plans. This can include, for example, your publication record, awards, presentations, inclusive research practices that promote the excellence of your research, and areas for future research.


Reference requirements
  • 3 required (contact information only)

Apply link:
https://aprecruit.berkeley.edu/JPF05214

Help contact: harrisonmd@berkeley.edu



About UC Berkeley

UC Berkeley is committed to diversity, equity, inclusion, and belonging in our public mission of research, teaching, and service, consistent with UC Regents Policy 4400 and University of California Academic Personnel policy (APM 210 1-d). These values are embedded in our Principles of Community, which reflect our passion for critical inquiry, debate, discovery and innovation, and our deep commitment to contributing to a better world. Every member of the UC Berkeley community has a role in sustaining a safe, caring and humane environment in which these values can thrive.

The University of California, Berkeley is an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.

For more information, please refer to the University of California's Affirmative Action and Nondiscrimination in Employment Policy and the University of California's Anti-Discrimination Policy.

In searches when letters of reference are required all letters will be treated as confidential per University of California policy and California state law. Please refer potential referees, including when letters are provided via a third party (i.e., dossier service or career center), to the UC Berkeley statement of confidentiality prior to submitting their letter.

As a University employee, you will be required to comply with all applicable University policies and/or collective bargaining agreements, as may be amended from time to time. Federal, state, or local government directives may impose additional requirements.

Unless stated otherwise, unambiguously, in the position description, this position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee.

As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct.



  • "Misconduct" means any violation of the policies or laws governing conduct at the applicant's previous place of employment, including, but not limited to, violations of policies or laws prohibiting sexual harassment, sexual assault, or other forms of harassment or discrimination, as defined by the employer.
  • UC Sexual Violence and Sexual Harassment Policy
  • UC Anti-Discrimination Policy
  • APM - 035: Affirmative Action and Nondiscrimination in Employment


Job location
Berkeley, CA
Applied = 0

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