Postdoctoral Associate - Neal Laboratory

About the role

The Neal Laboratory within the Broad Institute's Novo Nordisk Foundation Center for Genomic Mechanisms of Disease seeks an independent Postdoctoral Associate to integrate experimental biology, quantitative imaging, and computational analysis to uncover mechanisms of rare genetic diseases and translate those insights into potential treatments. The position is part of Project Encore, a new initiative funded by an NIH Director's Transformative Research Award. Encore is developing a scalable approach to therapeutic discovery for rare genetic diseases by combining barcoded disease-associated variant libraries, multiplexed cell imaging, and in situ barcode sequencing to measure how compounds affect protein localization and cellular organization across hundreds of variants in parallel. The project includes experimental screening of more than 1.6 million compound–variant combinations with the goal of identifying compounds that reverse disease-associated cellular phenotypes and generate testable therapeutic hypotheses. This role is for a scientist who wants to personally connect experimental design with computational discovery, tackling questions such as how a disease phenotype should be measured, what counts as a rescue, and how phenotypes and drug responses can be connected to identify shared biology between diseases. You will conduct experiments, develop and apply analytical methods, and use the resulting insights to choose and design the next experiments, building a research direction of your own. Meaningful hands-on experience in both experimental biology and computational analysis is required, although candidates need not have equal depth in both areas or prior experience with every platform-specific method.

Responsibilities

• Develop and lead research projects: identify questions that span experiments and analysis (e.g., which variants share mechanisms, how compounds reverse phenotypes) and develop them into projects you lead.
• Design and perform pooled optical screens: work with barcoded variant libraries, mammalian cell models, multiplexed staining, and in situ sequencing to generate informative single-cell imaging datasets.
• Develop reproducible analysis workflows: process imaging and barcode data, assess data quality, and generate quantitative cellular profiles using established tools and new approaches where needed.
• Evaluate methods for detecting phenotypes and rescue; apply statistical and machine learning approaches to distinguish variant-associated phenotypes, quantify compound responses, and compare conventional image features with learned representations.
• Connect computational predictions to experiments: design and conduct dose-response and disease-relevant validation experiments with experimental and clinical collaborators.
• Share and mentor: lead manuscript preparation and present findings, contribute open-source software and accessible datasets, and mentor junior researchers.

Requirements

• Ph.D. in computational biology, bioengineering, systems biology, biophysics, cell or molecular biology, or a related field.
• Substantial hands-on experimental experience, including mammalian cell culture, molecular biology, and fluorescence microscopy.
• Proficiency in Python and/or R, with experience independently analyzing biological datasets and implementing well-documented, reproducible analytical workflows.
• Demonstrated ability to connect computational findings with biological questions, communicate clearly across disciplines, troubleshoot research problems, and advance a research project independently, as shown by first-author publications or preprints.

Preferred qualifications

• High-content image analysis, quantitative cell profiling, or computer vision using tools such as CellProfiler or Pycytominer.
• Statistical modeling or machine learning for biological data, including supervised classification, deep learning, or self-supervised representation learning.
• Pooled genetic screens, lentiviral transduction, barcoded libraries, multiplexed imaging, or in situ sequencing.
• Cloud or high-performance computing environments for scalable analysis of imaging datasets.

Mentorship and career development

The Neal Laboratory emphasizes interdisciplinary training, scientific independence, and collaborative research. This position offers opportunities to develop expertise connecting experimental and computational approaches, with mentorship supporting academic and biotechnology career paths. Postdoctoral researchers are encouraged and supported in applying for external fellowships.

Schedule

Start date: flexible; as early as possible. Location: on-site at the Broad Institute, Cambridge, MA. Full-time, 40 hours per week.

Pay

Base pay range: $70,000.00/yr – $92,666.67/yr. Actual compensation varies based on relevant skills, experience, education, qualifications, and other factors permissible by law.

Benefits

Comprehensive total rewards package including medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending and health savings accounts; at least 13 paid holidays; winter closure; paid time off; parental and family care leave; and an employee assistance program, among other Broad benefits.