Senior Principal Scientist / Assoc Director, Oncology Translational Research

Novartis AG

Cambridge, MA

JOB DETAILS
SALARY
$138,600–$257,400 Per Year
SKILLS
Analysis Skills, Artificial Intelligence (AI), Best Practices, Bioinformatics, Biology, Biomarkers, Biomedical Engineering, Biomedical Research, Cancer, Computational Engineering, Cross-Functional, Data Science, Document Management, Documentation Standards, Drug Development, Drug Discovery, Image Processing, Informatics, Machine Learning, Medicine, Needs Assessment, Oncology, Operational Improvement, Pathology, Pharmacodynamics, Problem Solving Skills, Process Development, Process Improvement, Project Design, Publications, Python Programming/Scripting Language, Quality Control, Quantitative Analysis, Scalable System Development, Team Player, Technical Leadership, Translational Research
LOCATION
Cambridge, MA
POSTED
10 days ago

Location: Cambridge LI#Onsite The Oncology Pathology and Biomarkers group within Oncology Translational Research at Novartis Biomedical Research is seeking an accomplished Imaging Scientist to join the Image Analysis team in Cambridge.This role is for a scientific and technical leader with expertise in digital pathology, computational image analysis, AI/ML, and tissue-based oncology biomarkers. The successful candidate will develop and support scalable workflows for whole-slide pathology and multiplexed tissue imaging data.The position will expand OPB's AI-enabled image analysis capabilities and deliver scalable solutions for digital pathology and translational biomarker assessment across oncology programs.The scientist will support spatial analysis of tumor samples, help establish pipelines for RareCyte Orion high-plex imaging data, and strengthen harmonized HALO AI workflows across Cambridge and Basel.Key ResponsibilitiesDigital Pathology and Imaging StrategyDevelop and deploy scalable workflows for pathology whole-slide image acquisition, processing, analysis, and interpretationApply AI/ML and quantitative image analysis to address biological, translational, and biomarker questions in human and preclinical samplesProvide expertise in digital pathology, spatial analytics, and AI-enabled biomarker quantification across oncology programsEvaluate emerging computational imaging approaches that strengthen OPB biomarker capabilities and decisional data deliveryHALO AI Support and Cross-Site HarmonizationServe as a subject matter expert for HALO and HALO AI workflows and drive harmonization across Cambridge and BaselBuild robust, reproducible, and well-documented analytical processes that improve operational resilience and cross-site consistencyImprove image data organization, sharing, and best practices to support collaboration with Oncology Data Science, Data42, and enterprise AI initiativesAI/ML-Enabled Image AnalysisBuild, optimize, and apply AI/ML models and reproducible workflows for whole-slide, multiplexed, and high-plex tissue imagingUse tools such as HALO and HALO AI for segmentation, classification, feature extraction, spatial analysis, and biomarker scoringTranslate image-derived outputs into clear biological insights that inform project decisionsHigh-Plex Imaging and RareCyte Orion AnalysisDevelop and implement pipelines to process, analyze, visualize, and interpret RareCyte Orion and other high-plex imaging dataPartner with OPB scientists to define fit-for-purpose analytical approaches for multiplexed tissue imaging studiesIntegrate high-plex imaging outputs with broader biomarker and translational datasetsEstablish quality control, documentation, and reporting standards that support innovative use of multiplexed imaging in oncologyCross-Functional Collaboration and ImpactPartner with scientists, pathologists, physician-scientists, computational biologists, data scientists, and project teams to design, analyze, and interpret tissue-based studiesEngage across Oncology Translational Research and broader Novartis Biomedical Research to identify stakeholder needs, address workflow gaps, and implement practical solutionsCommunicate image analysis strategies, recommendations, and findings clearly to multidisciplinary teams while contributing to a collaborative culture of scientific excellence and innovationEssential requirementsThis is a dual posting. The final level of the offered role will be determined by the hiring team based on the skills, experience, and capabilities required to perform the role at the offered level.PhD or MS in biology, bioinformatics, biomedical engineering, computational biology, data science, pathology, or a related fieldMinimum 5 years of industry experienceSignificant experience in digital pathology, computational image analysis, imaging data science, translational oncology, or tissue-based biomarker researchExpertise with image analysis tools such as HALO and experience developing, implementing, and applying AI/ML models to tissue imagesDemonstrated success applying advanced imaging solutions to pathology and translational research workflows, including high-resolution whole-slide and gigapixel image datasetsStrong understanding of tissue-based biomarker development, oncology biology, and translational researchStrong organizational, communication, and problem-solving skills, with the ability to engage stakeholders, identify process gaps, and drive next stepsAbility to work effectively in multidisciplinary, matrixed teams and contribute in a collaborative, innovative, and self-directed wayDesirable QualificationsBackground in cancer biology, immuno-oncology, radioligand therapy, spatial biology, or tumor microenvironment biologyExperience supporting oncology drug discovery or early clinical development with image-based biomarker strategies and spatial scoring approaches for pharmacodynamic, indication, isotope, or patient selection decisionsFamiliarity with RareCyte Orion or other multiplexed/high-plex tissue imaging platforms, including machine learning and computational methods for tissue image analysisProficiency in Python or RExperience harmonizing digital pathology workflows across sites, teams, or software environments, with familiarity in image data centralization, digital pathology infrastructure, FAIR principles, or enterprise data platformsExperience collaborating with oncology data science, informatics, translational medicine, or enterprise AI teamsScientific visibility through publications, presentations, or collaborations in digital pathology, oncology biomarkers, image analysis, or spatial biologyNovartis Compensation and Benefit Summary: The salary for this position is expected to range between $138,600.00 - $257,400.00 USD Annual per year.The final salary offered is determined based on factors like, but not limited to, relevant skills andexperience, and upon joining Novartis will be reviewed periodically. Novartis may change the publishedsalary range based on company and market factors.Your compensation will include a performance-based cash incentive and, depending on the level of therole, eligibility to be considered for annual equity awards.US-based eligible employees will receive a comprehensive benefits package that includes health, life anddisability benefits, a 401(k) with company contribution and match, and a variety of other benefits. Inaddition, employees are eligible for a generous time off package including vacation, personal days,holidays and other leaves.

About the Company

N

Novartis AG

Novartis provides healthcare solutions that improve and extend people’s lives. We use science-based innovation to address some of society’s most challenging healthcare issues. We discover and develop breakthrough treatments and find new ways to deliver them to as many people as possible. Our company is focused on industry-leading divisions with innovation power and global scale: pharmaceuticals, eye care and generic medicines Novartis is headquartered in Basel, Switzerland. Novartis Group companies employ approximately 120,000 associates and its products are available in more than 180 countries around the world.

COMPANY SIZE
10,000 employees or more
INDUSTRY
Biotechnology/Pharmaceuticals
FOUNDED
1996