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At Roche, we believe it’s urgent to deliver medical solutions right now – even as we develop innovations for the future. We are passionate about transforming patients’ lives, and we are fearless in both decision and action. We commit ourselves to scientific rigor, unassailable ethics, and access to medical innovations for all.
Roche Pharma Research and Early Development (pRED) translates extraordinary science into medical innovation through a diversity of technologies and talent. The translational Modelling and Simulation (tM&S) capability, part of the Predictive Modeling (PM) Chapter, aims to enhance understanding of disease biology and inform the selection of the right molecules for development.
We are looking for a scientist to support early research and development with mathematical modeling. This role requires a candidate with a strong mathematical background and a pragmatic approach to drug development. You will design innovative quantitative approaches to predict clinical efficacy and safety, integrating pharmacological and toxicological data to ensure the optimal conduct of clinical studies.
Your mission will be to conduct modelling and simulation activities at the project level through the development of quantitative physiology/mechanism-based and drug-disease models. You will:
Develop multi-scale models for PK, efficacy, and toxicology by integrating experimental data (in vitro, in vivo, and omics) and literature-based evidence.
Build complex quantitative systems pharmacology (QSP) models, such as mechanistic tumor-site interaction models for small molecules, to predict drug disposition and target attainment.
Apply mechanistic insights to characterize drug accumulation and PK/PD relationships, including the impact of lysosomal trapping and binding dynamics.
Extend modeling frameworks to areas such as combination therapies, antibody drug conjugates and antibiotic PK/PD.
Design and deploy interactive tools, specifically using R and Shiny applications, to facilitate model exploration and guide internal decision-making.
Leverage AI and Machine Learning to enhance predictive accuracy, automate data integration, and explore high-dimensional biological datasets.
Perform rigorous parameter estimation through Bayesian methods and stochastic modeling techniques to extend deterministic frameworks.
Communicate results quickly and effectively to project teams and senior management, ensuring M&S activities align with overall project goals and Roche standards.
A PhD-level degree in natural sciences, mathematics, physical sciences, or engineering is required.
Advanced programming skills in R and Python, with a proven ability to code quickly and with high rigor are required.
Extensive experience in mechanistic modeling is required.
A strong mathematical foundation applied to drug discovery, with the ability to put complex results into the perspective of the drug development process is required.
An independent thinker with high creativity and a track record of scientific excellence is required.
Strong lead author history of publications and a history of effective scientific communication both inside and outside the company is required.
Inclusive mindset and the ability to interact effectively with pharmacology scientists, project leaders, and experimental collaborators.
Growth mindset characterized by curiosity and a willingness to learn and go beyond standard solutions and methods.
Willingness to speak up, bring different perspectives, and lead consultants or outside collaborators effectively.
Proactive attitude that takes initiative, proposes solutions, and maintains a "can-do" approach to complex scientific challenges.
Independent thinker with a track record of scientific excellence and a strong lead author history of publications.
The next step is yours. To apply today, click on the "Apply online" button.
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Roche is an Equal Opportunity Employer.