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Join Roche as a Senior Scientist in Computational Medicine to advance imaging data analysis and drive data-driven insights for clinical development. Collaborate with multidisciplinary teams to develop innovative analytical approaches and inform biomarker strategies, contributing to Roche's mission to prevent, stop, and cure diseases and ensure access to healthcare for generations to come.

Tasks

  • Formulate scientific questions and design computational analysis strategies in partnership with stakeholders across disease areas, clinical sciences, biomarker, and translational medicine.
  • Develop and apply state-of-the-art AI/ML approaches for biomedical imaging and multimodal data integration to derive quantitative, reproducible biomarkers.
  • Leverage modern AI technologies, including Generative AI and Agentic AI systems, to accelerate scientific workflows, automate complex analyses, and enhance decision-making.
  • Analyze biomedical imaging data from preclinical studies and clinical trials to support study design, patient stratification, biomarker development, drug differentiation, endpoint strategies, and portfolio decisions.
  • Develop, maintain, and document scalable, reusable computational workflows, software, and analysis pipelines aligned with global standards and best practices.
  • Represent the Imaging Data Insights team as a trusted, strategic partner; build collaborative relationships across the enterprise, align shared objectives, communicate findings effectively, and deliver collective portfolio impact.
  • Mentor junior scientists and contribute to fostering technical excellence, psychological safety, open feedback, inclusion, continuous learning, and a collaborative team culture.

Requirements

  • PhD in a scientific or technical discipline (e.g., computer science, biomedical engineering, applied mathematics, physics, or similar) or equivalent qualification, with 3+ years of professional experience in pharmaceutical R&D.
  • Deep expertise in biomedical image analysis, data science, AI/ML, or related quantitative disciplines, with experience developing computational workflows for quantitative imaging analysis.
  • Demonstrated ability to translate complex imaging and biological data into actionable insights that drive decision-making across the R&D value chain.
  • Ability to quickly grasp new scientific challenges, formulate clear problem statements, and deliver impactful solutions.
  • Proven ability to contribute to high-performing, multidisciplinary teams in cross-functional and interdisciplinary environments, foster an inclusive and purpose-driven culture, and influence effectively without formal authority.
  • Strong track record of building trusted, business-oriented partnerships across the enterprise and the broader scientific ecosystem.
  • Excellent communication skills, with the ability to explain complex technical concepts, provide scientific guidance, and influence diverse stakeholders.
  • A growth mindset with a passion for continuous learning, innovation, and adopting emerging computational technologies, including Generative AI and Agentic AI approaches to scientific discovery.
  • Strong expertise in biomedical imaging, imaging biomarker research, and advanced AI/ML methods across imaging modalities (e.g., MRI, CT, PET, DXA, ultrasound, ophthalmic imaging).
  • Expertise in quantitative biomedical image processing and analysis techniques, including image preprocessing, denoising, registration, segmentation, feature extraction, classification, quality control, and biomarker generation.
  • Experience with biomedical imaging software platforms and open-source ecosystems (e.g., FreeSurfer, FSL, SPM, 3D Slicer, Fiji/ImageJ, Napari, or equivalent) across one or more biomedical imaging domains, as well as with standard and proprietary biomedical imaging data formats (e.g., DICOM, NIfTI, vendor-specific formats) and associated metadata.
  • Proven programming proficiency in Python and/or R, including experience with deep learning frameworks (e.g., PyTorch, TensorFlow), scientific computing, and image analysis libraries (e.g., scikit-image, OpenCV, MONAI, SimpleITK).
  • Experience developing and applying Agentic AI systems, Generative AI, and foundation models to accelerate biomedical data analysis, augment scientific discovery, and automate scientific workflows.
  • Experience integrating multimodal data (e.g., imaging, clinical, digital health, omics, and real-world data) by means of cutting-edge multimodal AI approaches.
  • Solid understanding of statistical analysis, experimental design, model validation, uncertainty quantification, and quality assurance for biomedical imaging data and AI models.
  • Experience with software engineering best practices, including version control (Git), testing, reproducible workflows, containerization, and cloud or high-performance computing environments.
  • Focus, collaborative teamwork, and exceptional delivery are key behaviors for this role.
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Über uns
Roche ist ein international tätiges Schweizer Pharma- und Diagnostikunternehmen mit Sitz in Basel und entwickelt, produziert und vertreibt Medikamente sowie diagnostische Lösungen. Das Unternehmen ist in den Bereichen Pharma und Diagnostik tätig und fokussiert sich auf Forschung und Innovation in verschiedenen Therapiegebieten wie Onkologie, Neurologie und Infektionskrankheiten. Roche ist weltweit aktiv und zählt zu den führenden Unternehmen im Gesundheitsbereich.
Das Team

You will be a member of the Imaging Data Insights team within the Computational Medicine department, working with imaging experts located in Basel, Penzberg, and South San Francisco, and reporting to the Group Leader - Imaging Data Insights Europe. The team is collectively accountable for delivering critical data-driven insights that inform the portfolio and collaborates closely with other teams in Computational Medicine, Computational Biology, and disease area partners.

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