Embedded within the Broad Institute, the Center for the Development of Therapeutics (CDoT)) is a highly collaborative organization of professional drug discovery scientists. Our mission is to translate cutting edge biological insights originating from the Broad community into impactful drug discovery projects. We partner with faculty from MIT, Harvard, and the Harvard teaching hospitals together with industry partners in pharmaceutical, biotechnology and venture capital firms to validate druggable targets and identify leads. We combine our deep expertise in drug discovery with the knowledge and unique capabilities of the Broad Institute to explore drug discovery projects in a wide range of disease areas (including oncology, cardiovascular, psychiatry, infectious and rare diseases). We use systematic approaches in genomics, biology, high content imaging, chemistry, and machine learning coupled with the Broad's culture of creativity, risk taking, and open sharing, to successfully advance science and develop new treatments for patients.

We are seeking a passionate and highly motivated Senior Research Scientist to join CDoT’s High Content Imaging (HCI) team. This role is designed for an experienced scientist who thrives at the intersection of complex biology and high-throughput technology. You will be part of a collaborative team developing cutting edge high content imaging methodologies, including small molecule, genetic and chemical perturbation screening, to advance therapeutic and basic biology projects.

The ideal candidate blends deep technical expertise in molecular and cell biology, high content imaging and data analysis with a "systems-thinking" approach to operational efficiency and automation.

PRINCIPLE DUTIES AND RESPONSIBILITIES

Essential Functions

• Methodology Leadership: Drive the design, optimization, and implementation of next-generation HCI assays, including screening workflows.
• Scale & Automation: Partner with automation engineers to transition bench-scale assays into robust, high-throughput production pipelines.
• Cross-Functional Collaboration: Act as a technical bridge between cellular biologists, data scientists, and ML engineers to ensure data quality and biological relevance.
• Strategic Innovation: Evaluate and integrate emerging technologies in small molecule screening, perturbation biology and imaging to maintain the Broad’s competitive edge.
• Mentorship: Provide technical guidance and project leadership to junior scientists and research associates within the HCI ecosystem, management of scientists and/or research assistants.
• High content imaging expertise: High level of enthusiasm for exploring and implementing new molecular and cell-based technologies related to High Content Imaging.
• Work Style: Exceptional flexibility and a willingness to pivot strategies within a fast-paced, dynamic research environment.
• Communication: Ability to communicate complex technical concepts to diverse stakeholders, from public representatives, donors, and institutional leadership to cellular biologists, automation engineers, data scientists and software engineers.

Additional Desirable Capabilities

• HCI Software Ecosystem: Direct familiarity with High Content Imaging pipelines, specifically Revvity Harmony, Image Artist, and Signal applications.
• Automation & Robotics: Hands-on experience with high-throughput 384-well plate handling using a variety of liquid handling and robotic-based automation platforms.
• Optical Pooled Screening: Previous experience or theoretical grounding in OPS workflows and analysis.
• Advanced Analytics: Application of Machine Learning classification models to biological imaging data.

MINIMUM QUALIFICATIONS Required

• PhD in Molecular or Cellular Biology or related field with 5+ years of relevant experience
• Experience managing and/or mentoring scientists or research associates
• Extensive experience working with cells of diverse origins and various genetic/chemical perturbation approaches.
• Significant experience with genetic (CRISPR, RNAi) and chemical perturbations in complex cellular models.
• Significant experience developing phenotypic image-based assays suitable for small molecule or genetic screening
• A proven track record of working at scale and a keen appreciation for process optimization and reproducibility.
• Proven ability to process large-scale datasets, including expertise in:
• Preprocessing: Normalization, batch correction, and rigorous Quality Control (QC).
• Analysis: Data exploration and visualization using Dimensionality Reduction (e.g., UMAP, t-SNE) and Clustering.