Postdoctoral Researcher - Foundations of a Resilient Microbiome (2 Positions)

UC Santa Barbara; California; On-site; USD 60,000 - 80,000; Full time

Job summary

UC Santa Barbara's California NanoSystems Institute (CNSI) invites applications for two postdoctoral research positions in machine learning and computational modeling focused on identifying pathways involving the gut-brain axis that link the infant microbiome with neurodevelopment and Autism Spectrum Disorder (ASD).

This project is part of the Wellcome Leap FORM initiative and involves close collaboration between experiments, modeling, and lived experiences (Wellcome Leap Awards).

Qualifications

• PhD completed (or equivalent) in physics, CS, bioengineering, ecology, or a related field by application.
• Experience with machine learning and computational modeling in biological contexts.
• Interest in gut-brain axis and infant microbiome research.

Responsibilities

• Develop statistical and dynamical models based on metabolomic and metagenomic data.
• Collaborate across experiments, modeling, and lived experiences in a closed-loop format.
• Contribute to AI-powered digital twins and related computational work.

Skills

Machine learning

Computational modeling

Dynamical systems

Education

PhD completed in Physics, Computer Science, Bioengineering, Ecology, or related field

Job description

The University of California, Santa Barbara (UCSB) California NanoSystems Institute (CNSI) invites applications for two (2) Postdoctoral Research positions in machine learning and computational modeling, focused on identifying pathways involving the gut-brain axis that link the infant microbiome with neurodevelopment and Autism Spectrum Disorder (ASD). This project is part of the Wellcome Leap FORM initiative: Foundations of a Resilient Microbiome (Wellcome Leap Form) and involves closed-loop collaborations between experiments, modeling, and lived experiences (Wellcome Leap Awards).

Statistical and dynamical models will be developed based on metabolomic and metagenomic data obtained from experiments conducted in UCSB’s ExFAB BioFoundry for Extreme and Exceptional Fungi, Archea, and Bacteria (ExFAB website) in parallel with the modeling effort. Perturbation, dynamic trajectory, stability, and resilience analysis will follow a closed-loop format linking AI and dynamical models with experimental protocols and outcomes. The successful candidate will contribute to this work with freedom to pursue creative interests related to the project. They will have access to the broad multidisciplinary research environment at UCSB, including the REAL AI initiative, which focuses on developing AI-powered digital twins for complex systems, the Departments of Physics, Ecology, Evolution and Marine Biology, Psychology and Brain Sciences, the College of Engineering, and the Koegel Autism Center. Link to REAL Al website.

Applicants must have completed all requirements for a PhD (or equivalent) in Physics, Computer Science, Bioengineering, Ecology, or a related field, except the dissertation, at the time of application.