What are the responsibilities and job description for the Postdoctoral Fellow – Machine learning models for the analysis of digital sensor data position at UCLA Health?
Postdoctoral Fellow – Machine learning models for the analysis of digital sensor data
We invite applications for two postdoctoral fellow positions in the Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, USA. Our group focuses on developing and applying advanced machine learning approaches to underutilized biomedical datasets. The overarching goal is to improve outcome prediction and uncover new mechanistic biological insights and biomarkers relevant to human health.
Position Overview
You will develop and apply state-of-the-art methods to model the complexity of sensor data recorded from smartphones and smartwatches across diverse individuals to understand their relationship with mental health. You will have the opportunity to collaborate closely with computational neuroscientists, clinicians, and machine learning experts, while maintaining high levels of independence to explore your own research directions within the project.
Key Responsibilities
- Develop deep embedded clustering models for clustering individuals using digital sensor data
- Develop time-varying network inference models to analyze symptoms and behavior over time.
- Apply models to learn the relationship between digital sensors and mental health, with a focus on device usage in young adults.
- Disseminate results through publications, conference presentations, and open-source software tools.
Qualifications
Required:
- Ph.D. (obtained or expected) in Computer Science, Computational Neuroscience, Statistics, Mathematics, or related quantitative field.
- Strong background in machine learning, with hands-on experience in deep learning frameworks (e.g., PyTorch, TensorFlow).
- Proficiency in Python
- Demonstrated interest in applying AI/ML methods to biomedical questions and gaining in-depth knowledge of biomedicine.
- Track record of peer-reviewed publications.
- Ability to work both independently and collaboratively in an interdisciplinary environment.
Preferred:
- Proficient in software development practices and experienced with high-performance computing or GPU clusters.
- Biomedical and Electronic Health Records research
- Excellent communication skills for both technical and interdisciplinary collaborations.
About the Principal Investigator and Lab
The position will be in Dr. Veronica Tozzo's lab. Our research involves developing computational methods across various applications and data sources: single-cell hematological data for broad pathophysiological discovery with an emphasis on pregnancy, measurements of glycemia (e.g., continuous glucose monitoring) to enhance diabetes diagnosis and management, and digital phenotyping data to study depression. The lab values collaboration, innovation, and mentorship, providing opportunities for professional growth and independent project development. We welcome applications from diverse disciplines, cultures, countries, and backgrounds.
About UCLA and Los Angeles
UCLA is a leading research university located in the heart of Los Angeles, with a vibrant scientific community spanning computational medicine, genomics, and biomedical sciences. The Semel Institute for Neuroscience and Human Behavior fosters interdisciplinary collaboration between data scientists, biologists, and clinicians, providing state-of-the-art resources for machine learning and computational biology research. Los Angeles offers a dynamic urban environment with cultural diversity, natural beauty, and a thriving tech–biomed ecosystem.
Application Process
To apply, please submit the following as a single PDF:
- Cover letter describing your research background, career goals, and why you are interested in the position.
- Curriculum vitae, including a list of publications.
- Contact details for up to three references.
- Up to two representative publications or preprints with a description of your role
Review of applications will begin immediately and continue until the position is filled. The position is funded for at least three years, with a salary commensurate with NIH postdoctoral stipend levels.
Key papers:
- Tozzo et al. Statistical Models Coupling Allows for Complex Local Multivariate Time Series Analysis https://dl.acm.org/doi/abs/10.1145/3447548.3467362
- Douglas, et al. Assessing the feasibility of large-scale digital sensing for depression and anxiety: The Digital Mental Health Study https://www.medrxiv.org/content/10.1101/2025.10.01.25337105v1