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Data Scientist Computational Drug Safety EntryLevel/Experienced

AstraZeneca
Job LocationCambridge
EducationNot Mentioned
SalaryCompetitive salary
IndustryNot Mentioned
Functional AreaNot Mentioned
Job TypePermanent, full-time

Job Description

Data Scientist Computational Drug Safety (Entry-Level/Experienced)Every decision we make is rooted in the limitless possibilities of what science can do. From our laboratories to our marketing departments, our people work to realise the potential of how science can change lives.Youll join the Computational Drug Safety team within the Clinical Pharmacology & Safety Sciences, Data Science and Artificial Intelligence (CPSS/DSAI) (CPSS) function at one of AstraZeneca’s vibrant R&D sites; preferably in Cambridge, UK, or in Gothenburg, Sweden.Clinical Pharmacology & Safety Sciences (CPSS) is a function within Biopharmaceutical R&D, AstraZeneca’s small molecule biotech unit which delivers candidate drugs into late-stage clinical development. The role of CPSS is to characterize absorption, disposition, metabolism and elimination (ADME) properties of compounds, non-clinical toxicology and off-target pharmacology. Working in disease-focused project teams we help to discover efficacious molecules with good safety profiles. CPSS is committed to be an industry leader in supporting the discovery and non-clinical development of safe medicines that improve patients’ lives. Within CPSS, the Data Science and Artificial Intelligence (DSAI) team is dedicated towards developing computational models to aid projects to design and select molecules with the right safety and ADME profiles. This comprises the application of novel algorithms, the utilization of novel types of data, as well as the validation and deployment of models within the wider company.As a Data Scientist in our group, you will work with cutting edge technology in an open and collaborative environment nursing novel ideas. The group has strong focus on method development within the computational area, acknowledging the need of in depth understanding of the safety or ADME properties of interest. Collaboration within and outside CPSS is essential. Main Duties and Responsibilities

  • Application and development of Machine Learning / Artificial Intelligence and mechanistic modeling approaches to ADME and safety endpoints assuring delivery of appropriate tools and in silico models to projects for virtual screening, compound selection and experimental prioritization
  • Analyzing data and model quality ensuring high performance of models and tools
  • Providing specialist support for development, interpretation and application of machine learning models
  • Supporting analyses to provide mechanistic and translational insight into compound ADME and Safety profiles
  • Advancing the scientific field of computational safety, both within and beyond the company via eg peer-reviewed publications, presentations at conferences etc.
    • Requirements
  • PhD degree (or equivalent) in life science, computer science, or a related field; preferably with industry experience (the position can be filled flexibly at either entry or more senior level)
  • Demonstrated knowledge in one or more of the following areas
  • Expertise in a variety of machine learning methods (e.g. Deep Learning, SVM, Random Forest, Causal Reasoning, etc.)
  • Computational chemistry, Computational toxicology or Cheminformatics knowledge
  • Expertise in programming (particularly Python). Previous experience using cloud platforms would be beneficial
  • Previous evidence of scientific excellence (such as demonstrated in publications)
  • Excellent communication skills and ability to work in a multidisciplinary research environment
  • Innovative thinking, with passion, energy and drive
  • Open-minded, and ready to embrace new ideas and different perspectives
  • Strong critical thinking, planning, organizational and time leadership skills
    • Desirable
  • Biological understanding of toxicology and/or ADME endpoints
  • Experience in modelling ADME-related data
    • For more information please contact Andreas Bender AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

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