Associate Principal Scientist, Mechanistic Modeling in Neuroscience, Quantitative Pharmacology and Pharmacometrics
Associate Principal Scientists in the Neuroscience and Advanced Data Sciences group in the department of Quantitative Pharmacology and Pharmacometrics (QP2) apply quantitative approaches to develop and implement translational PK/PD (Pharmacokinetics/Pharmacodynamics) strategies, characterize clinical pharmacokinetics and pharmacodynamics of new chemical entities and biologics, and inform dose selection and go/no-go decisions. Associate Principal Scientists perform job duties independently with minimal supervision, support or lead QP2 efforts on neuroscience drug development programs, and author or co-author strategic documents.
Associate Principal Scientists are expected to have or be developing expertise in several areas, including:
Developing and executing mechanistic PK/PD models of neurodegenerative diseases, specifically physiologically-based pharmacokinetic (PBPK) and quantitative system pharmacology (QSP) models.
Keeping up to date with emerging literature and recognize potential application for the integration of mechanistic modeling and machine learning
Understanding different mathematical modeling frameworks and when they could be applied, such as Boolean networks, agent-based models, differential equations, and machine learning models.
Serving as an expert pharmacometric representative on drug development teams to design quantitative pharmacology studies and analyze data.
Collaborate with multidisciplinary project teams to support target identification/validation, therapeutic modality selection, drug candidate optimization, biomarker strategy, and clinical trial design.
Associate Principal Scientists demonstrate excellent leadership and communication skills. They collaborate within QP2 and with other functional areas, as well as with external vendors and partners, creating an aligned, quantitative framework to impact strategies and decisions of drug development teams.
(a Ph.D. or equivalent degree with a minimum 3 years of experience) OR (a PharmD or equivalent degree with at least 5 years of experience) OR (an MS or equivalent degree with at least 7 years of experience), where “experience” means having a record of increasing responsibility and independence in a similar role in pharmaceutical drug development or academia.
Educational background in mathematics, applied mathematics, engineering, pharmaceutical sciences, pharmacometrics, statistics/biostatistics, computational/systems neuroscience, or a related field.
Proficiency in MATLAB, R, Python or other similar programing language
Ability to comprehend scientific literature and write mathematical equations to describe biological/physiological processes.
Have strong organization skills and coding practices
Motivated to develop a career as a technical modeling expert in neuroscience with hands-on skills
Understanding of pharmacokinetics/pharmacodynamics and systems biology/pharmacology
Proficiency in performing mechanistic PK/PD modeling using standard pharmacometric software and programming languages (e.g. MATLAB, R, SimBiology, Monolix, Python)
Familiarity with computational neurosciences software and packages (e.g. GENESIS, NEURON, NetPyNE)
Familiarity with machine learning libraries and packages (e.g. TensorFlow, PyTorch, caret)
Strong skills in experimental design, mathematical problem solving, critical data analysis/interpretation, and statistics.
Proficiency in written and verbal communication, interdisciplinary collaboration, and problem scoping and planning.
Experience and disease knowledge in neuroscience
We are a research-driven biopharmaceutical company. Our mission is built on the simple premise that if we “follow the science” that great medicines can make a significant impact to our world. We believe that a research-driven enterprise dedicated to world-class science can succeed by inventing medicine and vaccine innovations that make a difference for patients across the globe.
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