Senior Scientist, Comparative Digital Pathology, Computational Biology and Medicine Full-time NEW

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The Position

In Roche´s Pharma Research and Early Development organisation (pRED), we make transformative medicines for patients in order to tackle some of the world's toughest unmet healthcare needs. At pRED, we are united by our mission to transform science into medicines. Together, we create a culture defined by curiosity, responsibility and humility, where our talented people are empowered and inspired to bring forward extraordinary life-changing innovation at speed.

The Computational Sciences Center of Excellence organisation will enable pRED to become more data-driven, more digitally adept and better prepared for the challenges of the future. Within the Center of Excellence, the Computational Biology and Medicine (CBM) department focuses on utilising and creating the latest Analytics & AI/ML approaches to improve our understanding of disease, disease progression, and individual patient response to treatment by having access to the largest Pharma R&D datasets in the world. In partnership with our scientists across Roche, we create better medicines by digitally augmenting every part of R&D through our data-driven culture.

The Opportunity:

This position will ensure that pRED is supported and enabled with world-leading computational biology capabilities. You will contribute to the BEAT (Biological Exploration and Analytics Technologies) subunit of CBM. This unit will be responsible for our contribution to the development, optimisation, and standardisation of workflows and advanced analytics approaches for core and emerging technologies in close collaboration with functional units including pRED PS Pathology. Together with your stakeholders you will contribute with the express aim of developing a competitive advantage for pRED through the application of computational biology to veterinary comparative digital pathology. Your success is measured by your contribution to the pRED/Pharma goals.

Digital pathology is a cornerstone of the ongoing digital revolution in pharmaceutical research. By enabling global collaboration, integrating AI-driven insights, and enhancing efficiency, digital pathology is reshaping how comparative pathologists contribute to drug discovery and development. As a computational scientist, your work would focus on developing and optimizing the technologies that underpin these advancements, ensuring they align with the unique needs of veterinary comparative pathology while driving innovation in pharmaceutical research.

In This Position You Will:

• Inform data and analytics strategy as a technical expert in collaboration with your primary stakeholders;
• Co-development and execution of pre-clinical pathology workflows for toxicologic pathology and research pathology to enable cross-species and translational research
• Represent BEAT as a trusted partner to our wider stakeholder ecosystem. You will follow the broader digital pathology research activities in the Center of Excellence.
• Commit to fostering an inclusive, purpose-driven, and collegiate workplace with a focus on collective action.
• Develop collaborative relationships with critical stakeholders to realise and elevate their strategic ambitions.
• Generate objective, high-value insights that inform and influence a continuously evolving strategy designed to ensure Computational Biology is a competitive advantage for pRED to deliver for the portfolio, and for patients.
• Provide technical guidance for a strategy for algorithm validation in the context of GLP and health authorities (e.g. FDA) guidelines/regulations;
• Maintain active awareness of technological and methodological developments to inform and direct strategic capability investment. Apply cutting edge multimodal approaches, including most recent computer vision technologies.
• Contribute to the optimisation of digital pathology business processes between digitisation, image management repositories and cloud compute solutions by operating with teams maintaining and developing these systems.
• Ensure data is reusable in an efficient way, alongside structured and accessible code, documentation, and reporting is essential. To ensure the traceability, integrity, and validation of the business process.

Who You Are:

• PhD in a scientific or technical field with 5+ years of experience in pharmaceutical R&D with deep knowledge in bioinformatics and biostatistics, data science, or related field. You have a deep and diverse understanding of biological profiling technologies, research microscopy, and workflow development. Knowledge of model species, comparative anatomy, and research applications is required.
• Experience in analysis of whole slide images (WSI), including HE, IHC, ISH, and multiplex, is a benefit
• Demonstrable evidence of contributing to high-performing and multidisciplinary teams. You contribute actively to create an inclusive, purpose-driven workplace.
• Strong ability to communicate and advise from your domain expertise within a dynamic setting
• Expertise in using biological data analysis to impact decision-making along the value chain; demonstrated ability to quickly grasp topics, formulate problem statements, and achieve successful outcomes
• You operate in a process-oriented way with your critical stakeholders in mind.

Toolbox:

Image Data Analysis and Optical Signal Processing

• Expertise in image processing techniques such as noise reduction, segmentation, and feature extraction from microscopy images, including brightfield, fluorescence, confocal, and electron microscopy.
• Strong proficiency in Python for data analysis and machine learning (e.g., libraries such as NumPy, SciPy, scikit-learn, TensorFlow, or PyTorch) is essential.
• Experience with R or MATLAB for statistical modeling and algorithm development.
• Experience with high-performance, parallel computing frameworks for handling large-scale imaging is essential.
• Familiarity with image analysis tools such as OpenCV, Fiji/ImageJ, and scikit-image for biological data and experience with commercial tools including Halo AI and Visiopharm AI is of benefit
• Ability to develop and apply deep learning models, like convolutional neural networks (CNNs), specifically for histopathological image analysis.
• Experience with model training for tasks such as tumor/lesion detection, grading, and feature extraction.
• Derivation of human interpretable features from WSI using deep learning models
• Supervised, weakly supervised, and unsupervised machine learning for the automated detection, classification, and quantification of cellular and tissue structures. Application of graph-based methods to derive relational insights from WSI.
• Performance evaluation: reproducibility, accuracy
• Familiarity with workflow development and optimization in cloud and distributed computational environments
• Familiarity with systems implemented to manage or migrate digitised slides

Unwavering focus, collaborative teamwork, and exceptional delivery are key behaviors that drive our mission of doing now what patients need next. Together, we can be transformative.

If you are passionate about contributing to a committed team and have the dedication to partnership and innovation, Roche is the place for you! Every role at Roche plays a part in making a difference in patients' lives. Apply now and join us in making an impact!