At AstraZeneca, we work together across global boundaries to make an impact and find answers to challenges. We do this with the utmost integrity even in the most difficult situations because we are committed to doing the right thing. We continuously forge partnerships that help pursue world-class medicines in new ways, combining our people’s outstanding skills with those of people from all over the globe!!

AstraZeneca are recruiting for an experienced Bioinformatician to work within our Translational Sciences, Oncology team. You will become a scientific lead for selected AstraZeneca programs and technology innovation. Within this position you will drive and support the development of strategies for a range of statistical analyses; by analysing and interpreting data. You must be a fully proficient Bioinformatician working with biostatistics, data mining, and data analysis in an academic or research environment. Experience in working with medical imaging data is definitely a plus.

Key Responsibilities and Accountabilities:

• Extract knowledge and insights from image-based data and other datasets (e.g., genome, proteome, transcriptome) in order to support drug development and biomarker discovery in Early Oncology through a range of data preparation, modelling, analysis and/or visualization techniques.
• Implement customized data analysis workflows based on our internal' platform technology as well as on external statistical analysis tools (e.g. R, Python).
• Provide scientific and technical leadership and support for projects including requirements engineering, development, implementation, deployment and result delivery.
• Lead, drive and support the development of strategies for a broad range of statistical analyses as well as results visualization.
• Analyze clinical data of early phase and registrational trials in concordance with relevant regulatory guidelines (GxP) and internal guidance documents.
• Work in close collaboration with translational scientists and pathologists to interpret analysis results.
• Establish and champion effective partnerships with data scientists, internal IT specialists and image analysis scientists doing technology and/or workflow improvements. Assist in engaging with collaborators in the identification of analysis goals, hypotheses and analysis options.
• Support scientific leadership status through publications.

Essential Requirements and Qualifications:

• M.Sc. or PhD in Computational Biology, Bioinformatics, Physics and/or related fields.
• Experienced at working on data analysis methods (using e.g. Python/R) and AI technologies in an academic or pharma research environment.
• Applied knowledge on clinical biostatistics e.g. Kaplan Meier analysis, feature selection, cross-validation and multiple testing.
• Experience with automated image analysis workflow and processes for histopathology images and a background in immune-oncology is advantageous.
• Experience in working with advanced machine learning techniques, e.g. graphs, convolutional neural networks is a plus.
• Experience in working with clinical data, its associated processes and best practices is beneficial.
• Needs to be adept at balancing multiple assignments in a timely manner and meeting assigned timelines.
• Scientific excellence and passion to work on innovative ways to data analysis challenges in Early Oncology.
• Talent to conceptualize, build, communicate and implement novel scientific ideas aligned with the drug development and biomarker strategies.

Date Posted

Closing Date

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 authorization and employment eligibility verification requirements.