The Savic Lab at UCSF is looking for Data Scientist who has the ability to manage multiple complex projects simultaneously. Equipped with cutting-edge technology to ensure the successfully delivery of projects, the incumbent will use advanced computational, computer science, data science, and CI software research and development principles, with a focus on computational biology, biological systems modeling, and pharmacometrics. We are looking to enhance the group’s platform development capabilit... more details
The Savic Lab at UCSF is looking for Data Scientist who has the ability to manage multiple complex projects simultaneously. Equipped with cutting-edge technology to ensure the successfully delivery of projects, the incumbent will use advanced computational, computer science, data science, and CI software research and development principles, with a focus on computational biology, biological systems modeling, and pharmacometrics. We are looking to enhance the group’s platform development capabilities with data scientists who come with more modeling, team work, coding, statistics, expertise. You will be responsible for developing and applying quantitative models to the discovery and development of therapeutic drug candidates. We are seeking modeling and simulation minded scientists to contribute to a team environment as we use diverse analytical and computational tools to characterize factors influencing the pharmacokinetic and pharmacodynamic properties of drugs. We need a dynamic and driven scientist who is able to: • Integrate quantitative approaches into drug discovery. • Conduct modeling and simulation to inform drug discovery and translation of drug properties. • Communicate quantitative data, both internally and in the scientific community. • Provide scientific leadership to research teams.
The final salary and offer components are subject to additional approvals based on UC policy.
To see the salary range for this position (we recommend that you make a note of the job code and use that to look up): TCS Non-Academic Titles Search (https://tcs.ucop.edu/non-academic-titles)
Please note: An offer will take into consideration the experience of the final candidate AND the current salary level of individuals working at UCSF in a similar role.
For roles covered by a bargaining unit agreement, there will be specific rules about where a new hire would be placed on the range.
To learn more about the benefits of working at UCSF, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html
PhD in Pharmacometrics, Pharmacokinetics/Pharmacodynamics, Clinical Pharmacology, DMPK, Pharmaceutics, Computational Sciences, Engineering, or a related field.
Advanced degree in Computer Science or related quantitative discipline, with strong training and experience in Computational Biology, Statistics, Machine Learning, Data Science, or Data Engineering.
Demonstrated track record of analyzing large biological datasets.
Demonstrated ability to initiate research proposals and acquire funding.
In depth skills and experience in independently resolving complex computing / data / CI problems using introductory and / or intermediate principles.
Bachelor's degree in Computer / Computational / Data Science, or Domain Sciences with computer / computational / data specialization or equivalent experience.
Minimum 5 years of related experience.
Industry or academic experience in PBPK, QSP, PK/PD, Clinical Pharmacology, exposure-response modeling, or other modeling & simulation related field
Experience using relevant software such as NONMEM, R, SimCYP, Monolix, Python, MATLAB, or similar.
Advanced knowledge of HPC / data science / CI / statistical methods.
Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences.
Demonstrated ability to regularly, effectively communicate with unit-level management.
Self-motivated and works independently and as part of a team.
In depth ability to successfully work and / or lead multiple concurrent projects. Demonstrated research and technology project leadership and management skills.
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