Remote Postdoc: Computational Neuroimaging for AD Prognosis

The University of Tennessee Medical Center Graduate School of Medicine; San Francisco (CA); On-site; USD 65,000 - 90,000; Full time

Job summary

UCSF seeks a highly motivated Post-Doctoral Research Associate to drive computational neuroscience modules of the ATLAS Consortium. You will apply multi-modal, systems biology approaches to predict individualized disease progression using longitudinal biomarker and imaging data, collaborating with an international team across the US, UK, and Spain.

This role emphasizes independent work in a remote, virtual setting, leading dissemination of methods and results, and contributing to grant-supported

Qualifications

• PhD awarded within the past three years in neuroscience, neuroimaging, computational biology, bioengineering, or closely related field.
• 2–5 years of relevant research experience in the field.
• Demonstrated expertise in complex statistical analysis, machine learning/AI, and scientific research.

Responsibilities

• Multi-Modal Data Integration with international team to harmonize imaging and biomarker data.
• AI/ML classifiers to impute neurodegenerative pathologies against autopsy ground truth.
• Lead/first author on methodological and clinical publications; present at major conferences.
• Contribute to community-scientist engagement and translation of prognostic predictions into tools.
• Maintain data quality and governance across harmonized datasets.

Skills

Statistical analysis

Machine learning

Communication

Project management

Education

PhD in neuroscience

Tools

Python

MATLAB

R

Bash

Job description

UCSF seeks a highly motivated Post-Doctoral Research Associate to drive computational neuroscience modules of the ATLAS Consortium. You will apply multi-modal, systems biology approaches to predict individualized disease progression using longitudinal biomarker and imaging data, collaborating with an international team across the US, UK, and Spain.

This role emphasizes independent work in a remote, virtual setting, leading dissemination of methods and results, and contributing to grant-supported