https://careers.astrazeneca.com/job/waltham/machine-learning-to-predict-cv-and-renal-outcomes/7684/16098217
Applications are invited for the post-doctoral fellowship opportunity described below in the Astrazeneca Clinical Pharmacology & Quantitative Pharmacology department Machine Learning to Predict CV and Renal Outcomes Locations: Waltham, Massachusetts, United States or Gaithersburg, Maryland, United States Job ID R-080721 Date posted 07/30/2020 APPLY<https://astrazeneca.wd3.myworkdayjobs.com/Emerging-Talent/job/US---Gaithersburg---MD/Machine-Learning-to-Predict-CV-and-Renal-Outcomes_R-080721-1> Do you want your work to truly make a difference? About the Postdoc Program: We're currently looking for talented scientists to join our innovative academic-style Postdoc. From our center in Gaithersburg, MD or Waltham, MA, you'll be in a global pharmaceutical environment, contributing to live projects right from the start. You'll take part in a comprehensive training program, including a focus on drug discovery and development, given access to our existing Postdoctoral research, and be encouraged to pursue your own independent research working with cutting edge Machine Learning/Data Science tools. What's more, you'll have the support of a leading academic advisor, who'll provide you with the guidance and knowledge you need to develop your career. This is an exciting area that hasn't been explored to its full potential, making this an opportunity to make a real difference to the future of medical science. About the Opportunity: We will use artificial intelligence tools and computational modelling to predict individual long-term risk of major CV events (MACE) and renal disease based on patient characteristics and short-term biomarker changes in a very large combined database of AstraZeneca's cardiovascular outcomes trials (patient-level data for ~180 000 individuals). This will facilitate treatment selection for patients with diabetes and cardiovascular disease by identifying characteristics that predict therapeutic response or non-response to different drug classes, inform patient selection and outcome definitions for future CV and renal outcomes trials, and characterize disease progression over time. If this sounds like you, apply now! Essential Education and Experience: * A PhD and/or a recent Postdoctoral fellowship in a quantitative discipline (pharmacometrics, engineering, pharmacology, computational biology, applied math, or related) * Success demonstrated by scientific publications and conference presentations * Interest in applying quantitative tools to solve clinically-meaningful problems Desirable Qualifications: * Working knowledge of biology and physiology * Experience working with clinical data Skills and Capabilities: * Proficiency and hands-on experience with data analysis, machine learning, and/or computational modelling in R or similar software * Ability to communicate technical material to a broad audience * Proven track record of effectively working independently, as well as within a team, to achieve results This is a 2-year program, which will be based in Gaithersburg, MD or Waltham (Boston), MA with a competitive salary/benefits on offer About AstraZeneca AstraZeneca is a global, innovation-driven biopharmaceutical business that focuses on the discovery, development and commercialization of prescription medicines for some of the world's most serious diseases. But we're more than one of the world's leading pharmaceutical companies. At AstraZeneca, we're proud to have a unique workplace culture that inspires innovation and collaboration. Here, employees are empowered to express diverse perspectives - and are made to feel valued, energized and rewarded for their ideas and creativity. Chris Penland, PhD Clinical Pharmacology & Quantitative Pharmacology __________________________________________ AstraZeneca R&D | Clinical Pharmacology & Safety Sciences 35 Gatehouse Dr, Waltham, MA USA 02451 T: +1 781 839 4618 M: +1 617 275 3769 chris.penl...@astrazeneca.com<mailto:chris.penl...@astrazeneca.com> Please consider the environment before printing this e-mail ________________________________ Confidentiality Notice: This message is private and may contain confidential and proprietary information. If you have received this message in error, please notify us and remove it from your system and note that you must not copy, distribute or take any action in reliance on it. Any unauthorized use or disclosure of the contents of this message is not permitted and may be unlawful.
