Postdoctoral Researcher - Age Rejuvenation Screening & Data Analysis

Buck Institute; Novato (CA); On-site; USD 80,000 - 100,000; Full time

Benefits offered by this job

Health insurance

Paid parental leave

Childcare assistance

401(k) with 5% employer match

Job summary

Buck Institute in Novato, California, is looking for a Postdoctoral Researcher specializing in microscopy-based image processing and data analysis. The role includes developing algorithms for high-throughput screening and maintaining analytical pipelines. A PhD in bioinformatics or computational biology is required, alongside Python proficiency and experience in automated image analysis. The position offers a competitive salary between $80,000-100,000 and a comprehensive benefits package, fostering a dynamic research environment.

Qualifications

• PhD required in bioinformatics, computational biology, or a related field.
• Experience with biological image processing and automated image analysis.
• Proficiency in Python and common scientific libraries.

Responsibilities

• Translate biological questions into analytical strategies.
• Build and maintain image-analysis pipelines.
• Support small-molecule screens and high-content imaging workflows.

Skills

Biological image processing

Automated image analysis

Python proficiency

Data analysis and biostatistics

Linux proficiency

Strong communication skills

Education

PhD in bioinformatics or computational biology

Tools

Deep-learning tools (CNNs)

GUI development in Python

Job description

Postdoctoral Researcher - Age Rejuvenation Screening & Data Analysis

POSITION SUMMARY The Ellerby and Gerencser labs at the Buck Institute seek a Postdoctoral Researcher (PhD required) with expertise in microscopy-based image processing, machine vision, and data operations supporting high-throughput small molecule screening. The lab integrates cell biology, advanced microscopy, robotic automation, and single-cell gene expression techniques to investigate cellular function in health and aging. Current efforts focus on defining youthful and aging-related cellular phenotypes to use in high-throughput screening efforts across multiple labs at the Buck Institute.

PROJECT OVERVIEW

This role involves developing and implementing algorithms, automated workflows, and analytical tools for modern microscopy and high-content imaging. Projects rely heavily on AI-based and classical segmentation methods, object detection, image registration, and object tracking. The lab uses automated microscopes and a fully robotic high-throughput screening system, generating large datasets requiring scalable, automated pipelines.

The candidate will:

• Translate biological questions into analytical strategies.
• Build and maintain image-analysis pipelines (deep learning and classical methods).
• Work with multiple data modalities, including compound‑library databases and phenotypic profiling datasets.
• Support small‑molecule screens, cell‑painting-based phenotyping, and high-content imaging workflows.
• Contribute to automation of data acquisition and experimental design.

Training will be provided in experimental technologies, and the candidate will also participate in experiment execution and data interpretation.

QUALIFICATIONS

Essential Requirements

• PhD in bioinformatics, computational biology, or a related field
• Experience with biological image processing and automated/pipeline-based image analysis
• Proficiency in Python and common scientific/imaging libraries
• Strong data analysis, database, and biostatistics skills
• Windows and Linux proficiency
• Demonstrated research portfolio or publication record
• Excellent written and oral communication skills
• Strong time‑management skills and the ability to work independently and collaboratively

Desired Skills

• Experience with data from high-throughput small-molecule screens
• Experience with laboratory automation and robotic systems
• Microscopic phenotypic profiling or cell-painting experience
• Deep-learning tools (CNNs for object detection, instance segmentation, embeddings)
• GUI development in Python (e.g., Flask, Voila)
• Pathway analysis or knowledge‑graph-based approaches
• Programming in R
• Experience with programmatic prompting of large language models

Compensation & Benefits

• Salary Range: $80,000-100,000 per year, depending on experience and qualifications
• Dynamic research environment using state-of-the-art techniques
• Comprehensive benefits package: health insurance, paid parental leave, childcare assistance, generous vacation/sick leave, and a 401(k) with 5% employer match
• Highly collaborative scientific and social community