Roche

Overview In this role, you will design, build, and deploy AI-driven solutions to enhance clinical trials and speed data-driven decisions in drug development. You will work within DEPCS, collaborating across clinical, data science, and engineering teams to deliver sensor-focused, AI-enabled digital solutions. You will transform raw sensor data into meaningful digital measures and implement robust ML and causal inference methods with rigorous validation. This position blends scientific impact with scalable software and regulatory-conscious practices, offering a chance to influence Roche’s clinical research platform and digital health ecosystem.

Verantwortungsbereiche Design and deploy AI-based solutions to improve clinical trials and evidence generation Analyze sensor time-series and other data to derive interpretable digital measures Transform raw sensor data from wearables into robust features and measures Develop advanced ML algorithms tailored to clinical trial data with strong validation and documentation Apply causal ML methods to support robust evidence generation Collaborate with clinical scientists, biostatisticians, biomarker leads, and engineers to integrate models into Roche workflows Present technical findings to diverse audiences and contribute to publications and internal knowledge Maintain awareness of ML trends in digital biomarkers and clinical AI Ensure reproducible research practices and audit-ready data handling Zentrale Anforderungen MSc or PhD in Computer Science, ML, Statistics, Electrical/Biomedical

Engineering or related field (preferred) 6+ years of experience in ML, signal processing or AI in biomedical, pharma, or healthcare settings Expertise in sensor data analysis, signal processing, causal inference, ML, statistics, probabilistic modeling; exposure to image analysis and CV Proven ability to bridge advanced analytics with rigorous statistical frameworks and reproducible research Proficiency in scientific programming languages; familiarity with HPC and ML experiment monitoring Experience with MLOps frameworks, Agile (e.g., Scrum) and regulated software development a plus Strong communication, problem-solving, teamwork, and ability to work in cross-functional teams communication problem-solving teamwork Python Git Docker