Senior Scientist, Informatics II

• Independently design, develop, optimize, and validate advanced machine learning, deep learning, and computer vision approaches for digital pathology, including cell and tissue segmentation, classification, feature extraction, and representation learning, to identify and quantify histopathologic features, cellular phenotypes, and spatial relationships.

•

, methodologies, and results clearly and effectively to scientific and cross-functional stakeholders through written and oral presentations.

• Maintain accurate and reproducible documentation of analytical workflows, algorithms, and results in electronic laboratory notebooks and project reports.
• Work independently and collaboratively within multidisciplinary teams to advance project objectives and deliver high-quality scientific results.

Qualifications

• PhD in computational biology, biomedical engineering, computer science, artificial intelligence, machine learning, computer vision, biomedical image analysis, or related quantitative discipline, with 4+ years of relevant applied experience.
• Strong foundation in mathematics, statistics, image processing, computer vision, and machine learning, with demonstrated experience developing computational methods and algorithms for quantitative image analysis.
• Demonstrated expertise in developing, optimizing, and validating image analysis and machine-learning approaches to extract quantitative features from H&E, immunohistochemistry, and/or multiplexed tissue imaging datasets.
• Strong proficiency in Python for scientific computing, image analysis, and machine learning, with experience using relevant libraries and frameworks such as NumPy, pandas, SciPy, scikit-learn, OpenCV, PyTorch, TensorFlow, or similar. Experience with R is desirable.

• Experience analyzing high-dimensional multiplexed imaging datasets, such as multiplex immunofluorescence, or imaging mass cytometry (IMC), including cell segmentation, cell phenotyping, feature extraction, and spatial analysis.
• Experience developing reproducible and well-documented computational workflows, including version-controlled code, structured data organization, and appropriate documentation of analytical methods and parameters.
• Experience with digital pathology image analysis platforms, such as Visiopharm and QuPath, with the ability to develop customized computational approaches when existing tools do not adequately address the scientific question.
• Excellent analytical, problem-solving, and communication skills, with demonstrated ability to work effectively across multidisciplinary teams and communicate complex computational concepts to scientific collaborators from diverse backgrounds.

• Strong background in immunology and tissue biology, or demonstrated experience applying computational image analysis to immunologic diseases. Experience with rheumatoid arthritis, inflammatory bowel disease, or related inflammatory conditions is particularly desirable.
• Strong understanding of spatial omics technologies and molecular pathology techniques, including immunohistochemistry, immunofluorescence, in situ hybridization, and related tissue-based assays.
• Experience integrating and analyzing multimodal spatial datasets, including combinations of histopathology, spatial proteomics, and spatial transcriptomics.
• Experience with contemporary computational pathology approaches, including deep learning, representation learning, or related AI-based methods for extracting biologically meaningful information from tissue images.
• Familiarity with cloud-based and/or high-performance computing environments, including AWS or similar computing infrastructure.
• Proficiency with data analysis and visualization tools, such as GraphPad Prism, Spotfire, Excel, or similar applications.
• Demonstrated curiosity and commitment to continuous learning and innovation, with an openness to new ideas, methodologies, and technologies and the ability to translate innovative approaches into practical scientific solutions.
• Self-motivated and highly collaborative, with a strong sense of ownership, scientific integrity, and commitment to quality.

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future. ​

• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.​

• This job is eligible to participate in our long-term incentive programs. ​

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company's sole and absolute discretion, consistent with applicable law.​

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