Bioinformaticist

Bioinformaticist I – Harvard Medical School

By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.

Harvard Medical School's mission is to nurture a diverse, inclusive community dedicated to alleviating suffering and improving health and well-being for all through excellence in teaching and learning, discovery and scholarship, and service and leadership. You’ll be at the heart of biomedical discovery, education, and innovation, working alongside world-renowned faculty and a community dedicated to improving human health. This is more than a job - it’s an opportunity to shape the future of medicine.

Our laboratory studies breast and ovarian cancer, striving to discover the mechanisms behind disease initiation, progression, and drug resistance. We are seeking a highly motivated Bioinformaticist with knowledge in computational image analysis and proficiency in Python. In this position, you will be supervised by our image analysis expert and will work together with members of the lab performing cyclic immunofluorescence (CyCIF) experiments.

As a Bioinformaticist, your primary responsibility will be analyzing fluorescent imaging data to quantify the levels of protein expression in individual cells and ‘cell neighborhoods’. This will involve identifying the appropriate single cell segmentation approaches for each tissue type and applying them iteratively to acquire fluorescence signal intensities that can be used to perform spatial analyses. You will interpret initial results, carry out follow‑up analyses, develop the necessary approaches, write code, and train other RAs on the project.

You will communicate findings to the lead investigator and collaborate to determine additional analyses needed. This position provides an opportunity to make significant contributions to many projects in our lab.

• Carry out image processing from tissue or tumor sections by registering and stitching images acquired on a Rarecyte microscope using a Python-based script and other approaches as they are developed.
• Perform fluorescent image processing, quality control, and cell segmentation using multiple approaches: identify appropriate single cell segmentation approaches for each tissue type and apply them iteratively, checking accuracy to obtain single cell data.
• Design, develop and test computational methods and displays to identify correlations between proteins expressed in single cells, to identify changes in protein expression in cells from tissues of women at high risk for cancer, and to identify differences in tumor responses to cancer therapies.
• Using biological knowledge, identify candidate cell neighborhoods to define using cellular protein expression, then implement appropriate computational approaches to define these neighborhoods (e.g., Latent‑Dirichlet Algorithm, network analysis, etc.).
• Work with scRNA‑Seq and spatial transcriptomics datasets, including probing gene signature expression and comparing expression between groups using correct statistical models (e.g., Linear Mixed Model, Bayesian).
• Interpret initial results and carry out follow‑up analyses, developing the necessary approaches and writing code for their execution; work with biologists on data analysis and with other bioinformaticists on the team to strategize computational approaches.
• Communicate findings with project collaborators, and prepare figures and materials for presentations as needed.
• Lead and train biologists and RAs on computational tools developed for segmentation and analysis.

• Bachelor’s degree in Biological Sciences or another related field.
• 3+ years of experience in the area of bioinformatics.

• Master’s in Bioinformatics, Biological Engineering, Computer Science or related field strongly preferred.
• Familiarity with computational image analysis strongly…