Associate Principal Bioinformatician, Quantitative Biology – Knowledge graph/network biology
At AstraZeneca we believe in the potential of our people and you’ll develop beyond what you thought possible. We make the most of your skills and passion by actively supporting you to see what you can achieve no matter where you start with us.
We have recently launched a Data Science and Artificial Intelligence (AI) transformation programme to position us at the forefront of our field over the coming years. This includes significant investment in groundbreaking machine learning and automation techniques, supported by an uplift in our data quality, standards and data engineering. We will:
- Advance our capabilities in Augmented Drug Design (ADD) for both small & large molecules – employing the very latest in machine learning and automation approaches to our Design-Make-Test-Analyse (DMTA) and biologics screening processes – leading to increased efficiency in lead identification, identification of novel molecules and higher clinical success rates
- Transform our ability to surface key Biological Insights through novel hypothesis generation algorithms deployed over complex knowledge graphs – leading to enhanced validation of our drug targets as well as the identification of new drug targets, and improving our understanding of the biological mechanisms underpinning disease
- Establish a robust Data Foundation for Science, ensuring our R&D data is F.A.I.R: Findable, Accessible, Interoperable & Reusable. The Data Foundation will implement common technologies, infrastructure & tools, along with the processes, standards & quality assurance – to make data “analytics & AI ready”. In scope is data from omics, clinical trials, ADD, imaging, literature, and real-world data, with more to be added over time
Help us to realize the unprecedented opportunities afforded by advances in data availability, computing power and AI to improve the way we discover and develop medicines, and to make a meaningful difference to patients’ lives.
Are you an experienced Bioinformatician looking for an exciting new challenge? Then why not join our Quantitative Biology team in Cambridge, UK and develop and apply computational solutions to help us evolve and extend our capabilities in graph-based data and information modelling and analysis, to support our drive to find medicines of the future. We are further investing globally in capabilities in knowledge graphs and network-based biology, and you will join a multi-disciplinary team of data scientists and researchers driving us forward in this area with the purpose of providing data-driven insights into biology for discovery of new therapies. Your role will be to work with diverse researchers to deliver graph modelling and processing of a range of data and information types, suitable for incorporation into graph-based systems, and deriving insights from their analysis.
As an Associate Principal Bioinformatician your main responsibilities will involve:
- Collaborating effectively with experimentalists, bioinformaticians, statisticians and other data scientists to explore, iterate, standardise and agree processes for modelling research data and information in graph format. You will be working as part of a global multi-disciplinary team.
- Contribute to, and where necessary prototype and build, software and analytical pipelines for wrangling, processing and modelling a variety of data and information types to enable graph-based modelling and capture
- Working with multi-disciplinary researchers to develop and refine research use cases, and define and capture data and information most relevant for a particular research need.
- Ensuring scientific excellence in software, processes and results as well as being efficient and well documented
- PhD, or equivalent experience, in bioinformatics, mathematics, computer science, statistics, engineering or the life sciences
- Demonstrable experience in the core competency areas: Modelling biological research data and information in graph format. Network biology. Graph-based database and query technologies. Use of ontologies and dictionaries.
- Experience with relevant computational tools such as R/R Shiny, Python, Shell, SQL/NoSQL databasing, networked and cloud based systems, software versioning tools (e.g. Git/Github), concept maps.
- Experience in biological research concepts, and data and information types (e.g. biological relationships, NextGen sequencing, genetics data)
- Ability to work effectively in global multi-disciplinary teams
- Strong communication skills, with technical and non-technical collaborators
- Experience in drug discovery and disease research would be an advantage
Location: Cambridge, UK
Salary: Competitive + Excellent Benefits
If you are interested, please apply.
Date job posted: 10th September 2019
End date for applications: 10th October 2019
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.