Job Description
We are seeking a highly motivated and detail-oriented Computational Biologist to join our team. This role focuses on designing and optimizing advanced image analysis algorithms to extract insights from high-dimensional spatial transcriptomics datasets. The ideal candidate will develop computational workflows, QC tools, and novel probe design algorithms while collaborating with Assay Development, R&D, and software teams to enhance assay productization and methodological innovation.
Who we are:
Spun out of Stanford and MIT, Stellaromics is an innovative biotech startup founded in 2022 and located in Boston, MA. Our pioneering proprietary technology helps researchers and clinicians create comprehensive cellular maps enhancing our understanding of various diseases, with our flagship product STARmap and upcoming Pyxa™ suite of products. We have a passionate management team and committed investors who believe in our patented technology and overall mission to profoundly advance biomedical research and accelerate the discovery of life-saving treatments.
Responsibilities:
- Design and optimize advanced image analysis algorithms, developing sequence-based bioinformatics solutions, and conducting spatial data analyses to extract meaningful insights from high-dimensional spatial transcriptomics datasets.
- Work closely with the Assay Development and R&D teams to develop and implement bespoke analysis pipelines that support both the productization of assays and the development of innovative methodologies.
- Design and implement computational workflows for spatial data interpretation and visualization.
- Develop QC tools to enable assay development scientists to efficiently interpret experimental data.
- Conduct benchmarking analyses to correlate spatial transcriptomics results with RNA-seq data.
- Design and optimize novel probe design algorithms for barcode-based spatial transcriptomics applications.
- Develop gene selection strategies for new tissue types using scRNA-seq datasets.
- Collaborate with software engineers and data scientists to integrate image analysis tools within cloud-based and on-premises computing infrastructures.
Qualifications:
Education and Experience
- PhD (or Masters with equivalent industry experience) in Computational Biology, Bioinformatics, Image Analysis, Computer Vision, or a related field.
- 2+ years of relevant experience with image processing techniques, preferably in a fast-paced, product-driven environment.
Technical Skills
- Proficiency in Python or another relevant programming language, with expertise in image analysis tools and libraries (e.g., OpenCV, scikit-image, ITK, ImageJ/FIJI, or CellProfiler).
- Hands-on experience with spatial transcriptomics, single-cell RNA sequencing, or related omics fields.
- Background in bioinformatics pipelines and tools for probe design, sequence alignment, and spatial data integration.
- Solid statistical and computational skills, with demonstrated experience in algorithm development for high-dimensional biological datasets.
- Background in machine learning techniques for image segmentation and feature extraction.
- In-depth understanding of fluorescence microscopy and multiplexed imaging technologies.
Soft Skills
- Proven ability to work collaboratively in an interdisciplinary research environment.
Additional Considerations
- Hands-on experience with secondary analysis tools for spatial transcriptomics is a plus.
- Submission of a GitHub profile link showcasing previous projects or contributions is encouraged.
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