Staff Scientist, Algorithm Development

Stellaromics Inc. • Boston, MA

36d

About The Position

We are seeking a highly skilled Staff Scientist, Algorithm Development to join our Computational Biology team. The ideal candidate will design, develop, and optimize computational methods to enhance 3D spatial transcriptomics analysis. In this role, you will leverage advanced statistical modeling and AI-driven frameworks to improve data accuracy, scalability, and performance. Additionally, you will collaborate across teams to align technical solutions with research and product goals while effectively communicating complex insights. This position will ideally be based at our headquarters in Boston, however we will consider applicants in the San Diego market.

Requirements

• Ph.D. in Electrical Engineering, Computational Biology, Bioinformatics, Computer Science, or related field with a strong emphasis on image and/or signal processing.
• 5+ years of relevant experience (industry or postdoctoral research) in image processing, digital signal processing, computer vision, statistical modeling, or machine learning.
• Demonstrated expertise in segmentation, registration, feature extraction, and signal processing techniques.
• Strong background in computer vision, statistical modeling, probabilistic methods, and unsupervised clustering, especially applied to imaging and signal data.
• Excellent command of Python and/or C++ for scientific computing with experience in relevant libraries (OpenCV, scikit-image, NumPy, etc.).
• Experience with deep learning frameworks (PyTorch, TensorFlow), high-performance computing, and large-scale data pipelines.
• Strong communication and documentation skills, with ability to manage and present complex data effectively.

Nice To Haves

• Proficiency in GPU computing; experience optimizing algorithms for GPU/parallel architectures is a strong plus.
• Experience in product development or translational projects in computational biology, medical imaging, or biotech is highly valued.
• Submission of a GitHub profile or portfolio of relevant projects is encouraged.

Responsibilities

• Lead the design, development, and validation of computational methods such as 3D image registration, spot detection, segmentation, decoding, and signal denoising to improve the accuracy and efficiency of spatial transcriptomics analysis.
• Develop advanced image and signal processing algorithms for object detection, feature extraction, spectral analysis, and noise reduction in complex multi-dimensional biological imaging datasets.
• Develop and optimize robust decoding algorithms to accurately assign transcripts from multiplexed, multi-round imaging data.
• Design statistical models for error estimation, dropout detection, and confidence scoring to ensure decoding reliability.
• Explore methods such as sparse coding, matrix factorization, probabilistic inference, and embedding-based machine learning to handle noise, optical crowding, and systematic artifacts.
• Explore and apply cutting-edge computational approaches, including deep learning (CNNs, VAEs, transformers) and generative AI models (e.g., denoising diffusion models) to improve both decoding and image analysis performance.
• Prototype novel algorithms for segmentation, denoising, decoding, and multi-round signal integration in large-scale 3D datasets.
• Optimize image processing and decoding algorithms for parallel processing, GPU acceleration, and FPGA implementations to enable real-time analysis of large datasets.
• Support integration of algorithms into scalable, high-performance pipelines for both research and product deployment.
• Collaborate across scientific, computational, and product teams to align technical solutions with product requirements and research goals.
• Communicate complex concepts in decoding, image analysis, and signal processing to diverse audiences, including customers.
• Provide domain expertise in spatial transcriptomics, single-cell analysis, image/signal processing, and statistical modeling to guide technical and strategic decisions.

Benefits

• Innovative Technology: Be part of a company at the cutting edge of spatial biology and genomics, revolutionizing the way researchers understand biology.
• Impactful Role: You will have a significant impact on the department and the future of the company.
• Collaborative Environment: Work with a talented, passionate team in a culture that values creativity, innovation, and teamwork.
• Career Growth: As a high-growth company, we offer significant opportunities for professional development and career advancement.
• An attractive compensation and benefits package based on market pay data will be commensurate with candidate skills, qualifications, and experience.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree