COAST PCL AI Research Scientist (California NanoSystems Institute)

Position overview

Position title: COAST PCL AI Research Scientist

Salary range: A reasonable salary range that the University expects to pay for this position at 100% time is $81,200 - $124,800.

Percent time: 100%

Anticipated start: October 1, 2026 or later

Position duration: 1 year, 100% appointment with possibility of renewal on an annual basis.

Application Window

Open date: September 4, 2026

Next review date: Wednesday, Sep 30, 2026 at 11:59pm (Pacific Time)

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

Final date: Monday, Apr 5, 2027 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

• COAST PCL AI Research Scientist *

The Computation-Optimized Automated Soft materials Technology Programmable Cloud Laboratory Node (COAST PCL), funded by the National Science Foundation, is a national AI-driven materials innovation infrastructure that combines autonomous robotics, advanced scientific instrumentation, and AI-guided experiment planning. This research ecosystem connects the broad and disparate communities of Materials, Chemistry, Engineering, and Computer Science, and enables rapid discovery and manufacturing of materials with highly controlled and programmable composition, properties, and functionality.

COAST PCL is seeking a motivated individual to grow a world-class resource for AI-guided autonomous experimentation and to take a lead role in the development and application of these next-generation methods in advancing COAST PCL's research mission and enabling a national user base to utilize this resource.

The AI Research Scientist will:

• Lead the artificial intelligence and machine learning capability at COAST PCL
• Spend 70% time, in tandem with the in-house research team, on making significant and creative contributions to in-house research
• Publish scientific papers, present at technical conferences, and file IP disclosures
• Collaborate with in-house Senior Faculty participants, postdoctoral fellows, and graduate student researchers to continuously build expertise and remain at the forefront of their research fields
• Gain fluency in the operational aspects of the facility's automated platforms, in the science those platforms enable, and in advances to the state of the art in autonomous experimentation, active learning, and agentic systems that should be leveraged as the facility evolves
• Build expertise by attending and presenting at regular research meetings with affiliate researchers, and providing consultation on model selection, experimental design, and data interpretation
• Consult with external users to develop a Project Feasibility and Research plan
• Review topically relevant COAST PCL user proposals and advise on technical feasibility
• Devote 30% time to serve as a scientific and technical expert and train external users in the facility's experiment-planning tools, data schemas, and analysis workflows
• Design and teach a training module as part of the COAST PCL Summer School and other similar workshops that will serve to highlight the facilities and research capabilities and promote use by internal and external users
• Responsible for the strategic growth of the facility's computational capability
• Collaborate with the robotics team to close the loop between predictive models and physical execution

Above all, COAST PCL seeks an individual who is passionate about contributing to cutting-edge scientific research. Genuine excitement for the cloud laboratory mission is essential to the success of the AI Research Scientist.

Qualifications

Basic qualifications (required at time of application)

• Ph.D. in Materials Science, Physics, Chemistry, Chemical Engineering, Computer Science, or a related field at the time of application.

Preferred qualifications

• Hands-on experience applying machine learning, optimization, and/or statistical modeling to scientific data and/or databases.
• Proficiency in Python. Strong programming skills, with proficiency in Python required. Knowledge in other languages (e.g. C, C++, R, Java, and/or Rust) is encouraged.
• Experience in working with scientific computing ecosystems and/or libraries (e.g. HPC clusters, cheminformatics tools such as RDKit). Competency in CUDA or other GPU APIs is highly desired but not required.
• Familiarity with laboratory automation principles, self-driving labs, and/or robotic experimentation platforms.
• Experience with sequential/active learning, clustering algorithms (e.g. KNN, random forests), Bayesian optimization, and/or design-of-experiments methods.
• Track record of peer-reviewed publications and/or deployed scientific software.
• Ability to work collaboratively in a team-oriented work environment.
• Ability to work creatively and independently and follow through on assignments with minimal or no direction.
• Excellent interpersonal and communication skills to interact with faculty, staff, students, visitors, and the public, and to communicate technical results clearly to a multidisciplinary audience.
• Skilled in project management, prioritizing workload, assessing timelines, and coordinating numerous assignments/projects simultaneously under heavy workload.
• Ability to utilize a variety of communication methods to move projects forward in a timely manner.
• Experience building agentic or tool-using LLM workflows and integrating them with external systems, such as instrument APIs.
• Experience establishing data pipelines and structured, ML-ready data models adherent to FAIR principles.
• A materials science- or physics-based foundation paired with demonstrated interest in machine learning and AI development, or strong machine learning experience with genuine motivation to work on physical-science problems.

Application Requirements

Document requirements

• Curriculum Vitae - Your most recently updated C.V.

• Cover Letter

• Statement of Research

Reference requirements

• 3-5 required (contact information only)

Applicants must submit contact information (telephone and email address) for 3-5 references. After interviews are completed, references will be contacted for finalists.

Apply link: https://recruit.ap.ucsb.edu/JPF03148

Help contact: debbie@cnsi.ucsb.edu

About UC Santa Barbara

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 for Employees, students and third parties
• APM - 035: Affirmative Action and Nondiscrimination in Employment

Additionally, you will be required to comply with the University of California Policy on Vaccination Programs, as may be amended or revised from time to time. Federal, state, or local public health directives may impose additional requirements.

The University of California 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, protected veteran status, or other protected status under state or federal law.

Job location

Goleta, California (UCSB OASIS)