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 computer vision algorithms 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.
Responsibilities:
  • Lead the design, development and validation of computational methods—such as 3D image registration, spot detection, segmentation, and decoding—to improve the accuracy and efficiency of 3D spatial transcriptomics analysis for various tissue types.
  • Leverage advanced statistical modeling and data science techniques to interpret high-dimensional biological data.
  • Support integration of advanced algorithms into scalable, high-performance analysis pipelines.
  • Explore and apply cutting-edge frameworks (e.g., variational autoencoders, transformer architectures, and generative AI models such as denoising diffusion models) for improved data analysis and model performance.
  • Proactively ensure efficient execution by optimizing algorithms for parallel processing, including GPU acceleration where appropriate.
  • Collaborate effectively across teams to align technical solutions with product requirements and research objectives.
  • Communicate complex concepts and findings clearly and effectively, both verbally and in writing, to a variety of audiences, including customers.
  • Provide technical expertise in spatial transcriptomics and single-cell data analysis to inform strategic decision-making.
Qualifications:
Education and Experience
  • Ph.D. in Computational Biology, Bioinformatics, Computer Science, or a related field.
  • 5+ years of relevant experience in image analysis, statistical modeling, genomics/transcriptomics, and machine learning, preferably in a fast-paced, product-driven environment.
Technical Skills
  • Demonstrated expertise in advanced statistical methods, including probabilistic modeling and unsupervised clustering.
  • Excellent command of Python and/or C++ for scientific computing and data analysis.
  • Experience with deep learning frameworks (PyTorch/ Tensorflow), high performance computing and large-scale data processing.
  • Knowledge of spatial modeling and analysis is a strong advantage.
  • Proficiency in GPU computing and experience designing algorithms optimized for parallel processing on GPU architectures is a plus.
Soft Skills
  • Excellent verbal and written communication skills, with the ability to document and manage data efficiently.
Product Development
  • Strong preference for candidates with practical experience in product development and a history of meeting project deadlines.

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