Diagnostic Scientist - Digital & Artificial Intelligence

  • AstraZeneca
  • Cambridge CB2 8PA, UK
  • 05/06/2021
Full time Data Science Data Analytics Big Data Artificial Intelligence Data Management Statistics

Job Description

Join the team dedicated to Oncology, with an ambition to eliminate cancer as a cause of death. It’s our big vision that unites and inspires us.

With multiple indications and high-quality molecules at all stages of our innovative pipeline, we keep pushing forward. Fusing ground breaking science with the latest technology to achieve breakthroughs. Backed by investment, we are seeking to deliver 6 new molecular entities by 2025.

A place built on courage, curiosity and collaboration – we make results-oriented decisions driven by patient outcomes. Empowered to lead at every level, free to ask questions and take smart risks that write the next chapter for our pipeline and Oncology team.

Pioneers of collaborative research we have built an outstanding scientific community both internally and externally. Fusing academia and industry, we have united some of the world’s foremost medical centres.

Have the opportunity to build an exciting and meaningful career as part of the team committed to improving the lives of millions with cancer.

Precision Medicine and Bio Samples within AstraZeneca focuses on matching medicines to those patients who will benefit from them most and delivers companion or complementary diagnostic assays that align with the drug development process and enable personalised healthcare approaches within our clinical portfolio.

Are you interested in applying your expertise in Machine Learning (ML)/Artificial Intelligence (AI) to implement digital solutions in clinical settings?

The Tissue Diagnostics team within Precision Medicine and Biosamples are seeking for candidates to lead or support initiatives that aim to bring about the value of ML/AI in clinical trials and in the real-world to help clinicians identify patients who might benefit most from AstraZeneca drugs.

In this role, you would work in multidisciplinary teams and be accountable for (1) identifying and evaluating technologies relying on ML/AI which can seek difficult challenges in precision medicine; (2) delivering the scientific aspects of developing and establishing ML/AI-based solutions in drug clinical trials; (3) producing scientific evidence enabling the development of diagnostic tests, their regulatory submissions and their commercial launches.

Typical Accountabilities

  • Managing projects in a global multi-disciplinary environment, applying scientific, technical and operational expertise. Identify opportunities, propose solutions and work across scientific boundaries to enable drug and diagnostic development projects.
  • Delivering digital solutions including ML/AI-based solutions to enable tissue-based diagnostic testing in clinical trials. This may involve working collaboratively internally and externally with AI companies to develop solutions, with clinical operations scientists to implement and troubleshoot solutions in clinical testing laboratories, and with regulatory, commercial and medical affairs teams to deliver applications to patients and clinicians.
  • Performing data analytics projects end-to-end to generate scientific insights that will guide our drug and diagnostic development programs.
  • Communicating scientific results internally and externally in conferences and in peer-reviewed publications.
  • Being accountable for the time and quality of agreed work.
  • Providing updates on the progress, risks and opportunities of the agreed deliverables to the appropriate governance bodies for review, challenge and issue resolution.
  • Taking on small supervisory or skills transfer / training roles.

Essential

  • Mater degree or equivalent experience in a relevant area
  • Experience working in a collaborative environment
  • Excellent verbal and written communication skills, ability to communicate scientific concepts to non-experts
  • Knowledge of statistics and/or machine learning
  • Programming skills in Python and/or R
  • Experience with data science libraries such as numpy, pandas, pytorch, tensorflow/keras, scikit-learn, seaborn, tidyr, caret, ggplot, shiny (cited libraries are examples, knowledge of these specific libraries is not a requirement).
  • Experience with tools enabling reproducible data science such as notebooks (e.g. Jupyter, R Markdowns) and version control (git or similar)

Desirable

  • PhD or equivalent experience in a relevant area
  • Experience applying machine learning to solve difficult questions in medicine
  • Familiarity with digital pathology and/or biomedical image analysis
  • Familiarity with cloud computing services such as Amazon AWS or Microsoft Azure
  • Knowledge about tissue-based diagnostic tests (e.g. immunohistochemistry
  • or in situ hybridization) is a plus but not a requirement

Why we love it

If your passion is science and you want to be part of a team that makes a bigger impact on patients’ lives, then there’s no better place to be. Here we truly understand science and apply it every day to strengthen and grow our pipeline.

So, what’s next?

  • Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you.
  • Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours.
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Where can I find out more?

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