Assistant Professor - AI for Biology

University of California Berkeley; Berkeley (CA); On-site; USD 111,000 - 163,000; Full time

Job summary

University of California Berkeley invites applications for a tenure-track Assistant Professor in AI for Biology within EECS and the Center for Computational Biology. The appointment focuses on developing novel AI/ML methods to advance understanding of biological systems, with emphasis on interdisciplinary collaboration and education across departments.

Applicants should hold a doctoral degree by start date and demonstrate a strong research program in AI for biology, with potential for teaching

Qualifications

• Completion of a doctoral degree (e.g., PhD) or equivalent international degree, or enrolled in a doctoral degree or equivalent international degree-granting program at the time of application.
• Preference will be given to applicants with AI/ML research in biology and potential for cross-disciplinary impact.

Skills

AI for biology

ML for biology

Genomics

Education

PhD or equivalent

Job description

Assistant Professor – AI for Biology – Electrical Engineering & Computer Sciences and Center for Computational Biology

Position overview

Position title: Assistant Professor

Salary range: The current salary range for the Assistant Professor position is $111,400-$163,200 (9-month academic year salary); however, off-scale salary and other components of pay, which would yield compensation that is higher than this range, are offered to meet competitive conditions.

Anticipated start: July 1, 2027

Application Window

Open date: September 25, 2026

Next review date: Monday, Nov 9, 2026 at 11:59pm (Pacific Time)

Final date: Monday, Nov 9, 2026 at 11:59pm (Pacific Time). Applications will continue to be accepted until this date.

Position description

The Department of Electrical Engineering & Computer Sciences (EECS) and the Center for Computational Biology (CCB) at UC Berkeley invite applications for one approved tenure-track position at the Assistant Professor level in the area of artificial intelligence (AI) for biology. Memberships in related institutes and initiatives or affiliations with other UC Berkeley departments or schools may also be considered. The EECS Department and the Center for Computational Biology have several related faculty positions open or opening soon. Please visit our EECS Faculty Positions website and the CCB Careers website to view these listings. If you are qualified for and wish to be considered for more than one position, please submit a separate application for each.

About the Department

The EECS department is part of the College of Engineering (COE) and the College of Computing, Data Science, and Society (CDSS). It offers one of the strongest research and instructional programs in this field anywhere in the world. The department's key strength is its array of cross-disciplinary, team-driven projects. The integration of EE and CS forms the core, with strong interactions that extend into many other disciplines.

About the Center

CCB is an academic unit under the College of Computing, Data Science, and Society (CDSS). It offers a PhD degree program, as well as interdisciplinary collaboration and research for diverse areas across computational biology. The center features distinguished faculty and graduate students from more than a dozen academic departments across six colleges at UC Berkeley.

About the Position

EECS and CCB are seeking applicants developing innovative AI and machine learning (ML) methods that significantly advance our understanding of complex biological systems and address high-impact problems in biology. Relevant research areas include, but are not limited to the following: AI/ML for predicting cellular phenotypes and responses to genetic, molecular, and environmental perturbations; modeling of molecular interactions, including interactions among proteins, nucleic acids, and small molecules; genotype-to-phenotype prediction across molecular, cellular, and organismal scales; AI/ML for genome and biomolecule engineering; and method development for computational genomics, including the integration of large-scale single-cell, spatial, imaging, and multimodal biological data. Across these areas, we are particularly interested in candidates who develop novel and broadly applicable AI/ML methodology for learning from complex biological data, with the potential to uncover fundamental biological principles and enable new approaches to understanding, predicting, and manipulating biological systems.

UC Berkeley values the family needs of faculty, including dual career couples, single parents, or those who may have taken time off for family reasons. For information about potential relocation to Berkeley, or career needs of accompanying parents and spouses, please visit the Office for Faculty Equity and Welfare's website.

Qualifications

Basic qualifications (required at time of application)

Completion of a doctoral degree (e.g., PhD), or equivalent international degree, or enrolled in a doctoral degree or equivalent international degree-granting program at the time of application.

Preferred qualifications

Preference will be given to applicants interested in AI and machine learning methods development that advance the understanding of complex biological systems as well as to applicants whose research, teaching, or service has prepared them to contribute to our commitment to create, educate, and serve our society.

Application Requirements

Document requirements

• Cover Letter
• Curriculum Vitae - Your most recently updated C.V. with complete list of publications. Please list prior academic, professional and/or public service activities and future service interests. This can include, for example, participating in professional or scientific associations, serving on committees that advance department, campus or discipline goals, and conducting outreach activities that can remove barriers and increase participation of academics in your field.
• Statement of Research - Please discuss prior research accomplishments and future plans. This can include, for example, your publication record, awards, presentations, inclusive research practices, communication skills, and collaborations that promote the excellence of your research, and areas for future research. Maximum of five pages, excluding references.
• Statement of Teaching and Mentoring - Please discuss prior teaching experience, teaching approach, and future teaching interests. This can include, for example, specific efforts and accomplishments, and future plans to support the success of all students through inclusive curriculum, classroom environment, and pedagogy. Please also discuss your mentoring experiences and approach. This can include, for example, past efforts and future plans to support the success of all students, and to foster an inclusive research mentoring environment that removes barriers and promotes equitable access and advancement of the research program. You might include a list of UC Berkeley courses you would feel comfortable teaching.
• Significant Publication 1 - Please provide a statement that summarizes the significance of the selected publication and include the PDF hyperlink.
• Significant Publication 2 - Please provide a statement that summarizes the significance of the selected publication and include the PDF hyperlink.
• Significant Publication 3 - Please provide a statement that summarizes the significance of the selected publication and include the PDF hyperlink.
• Authorization to Release Information Form - An institutional reference check will be completed only if you are selected as the candidate to whom the hiring unit would like to extend a formal offer. Download, complete, sign, and upload the Authorization to Release Information form.

Reference requirements

• 3 letters of reference required

Applicants must provide three letters of recommendation that speak to their record and/or potential for excellence in research, teaching, mentoring, and service. Recommender providing letters of reference should submit them as early as possible, preferably by the application deadline. Applicants are responsible for asking their references to upload letters as part of the online application process.

Job location

Berkeley, CA

Equal Opportunity

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.

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.

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.

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: Aff a