Research Bioinformatics Scientist (Level II or Senior)
At AstraZeneca, we are constantly pushing the boundaries of science to deliver life-changing medicines to patients, with a real passion for discovery and a pipeline to show for it. Here, you’ll have the opportunity to make a difference in people’s lives every single day.
AstraZeneca is looking to invest in the data management and analysis platforms underlying its existing and emerging drug discovery platforms, through its long term Growth Through Innovation Strategy. Within the new Data Science and AI Group, you will be working with colleagues to build data management and analysis foundations for the future.
The Research Bioinformatics Scientist II or Senior Research Bioinformatics Scientist is primarily responsible for advancing scientific knowledge through the use and development of Bioinformatics tools and approaches and applying that knowledge to drug development programs and innovative research. The candidate will have a strong background in analyzing quantitative MS-based proteomics or metabolomics data. Direct experience developing analytical techniques and data integration methodologies in support of biomedical research is required. The successful candidate will work closely with the expanding proteomics, metabolomics and protein biochemistry group using state-of-the-art Omics technology to investigate a number of biological questions. This is a key bioinformatic position that requires comprehensive expertise and hands-on experience in this area to support drug development projects.
This role will have the opportunity work in the areas of target identification and validation. The successful candidate, working with members of the bioinformatics team, will be responsible the delivery of data processes, tools, and methods to manage proteomics and metabolomics information and knowledge. This role resides within R&D and will work collaboratively within Bioinformatics and across therapeutic areas and functions to design, develop, and implement tools, systems, and methods to facilitate the mining of large complex multi-platform datasets and advance our understanding of disease.
About this Role
AstraZeneca has 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 cutting edge 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.
Major Duties and Responsibilities
- Develop the data infrastructure such as data pipelines and management solutions to expedite the generation and analysis of wide variety of proteomics and metabolomics studies, in conjunction with the scientists and data engineers.
- Support the multiomics data discovery activities through the design and delivery of novel algorithms, tools and techniques including feature detection, machine learning and intelligence.
- Conduct the analysis of proteomics and metabolomics data from projects at different stages of drug discovery and development. The analysis may include data ingestion, QC, pipelining, integration, functional interpretation and visualization.
- Provide technical support on the design and implementation of meta data model, data management, curation and integration solutions for proteomics, metabolomics, genomics and other datasets in conjunction with R&D and external partners.
- Provide training and advice to project scientists on optimal use of key data, analysis.
- Build and manage effective relationships to ensure utilization of information resources and services. Assist with the evaluation and implementation of new and existing data and analytical systems.
- Provide subject matter expertise and share knowledge on computational biology tools, experimental design, data analysis methodologies, data interpretation, and novel approaches to support target discovery and validation.
- Promote a culture of knowledge sharing across domains to proactively support sharing of best practices among informatics and science teams.
- Actively identify and progress opportunities to collaborate externally in support of departmental scientific and technical goals
- You have to demonstrate a proven record of being a fast learner, excellent communicator and thoughtful team member.
- You should be highly motivated, innovative, detail-oriented, creative, well organized and able to work independently when designing and executing analyses and will be expected to manage and prioritize several different projects and tasks in line with the objectives of the group.
Education, Qualifications, Skills and Experience
Ph.D. in Bioinformatics, Computational Biology, Systems Biology or related field is required.
Essential Skills & Experience:
- For Scientist II - PhD with 2 to 4 years of postdoctoral experience within a pharmaceutical/biotech company, academic or other relevant biomedical research environment required,
- For Senior Scientist - PhD with 5 to 8 years of postdoctoral experience within a pharmaceutical/biotech company, academic or other relevant biomedical research environment required
- Proficiency in common programming/scripting languages (e.g. R, Python, SQL, JAVA, C++, .NET) and their application in biomedical research.
- Demonstrated understanding in the methods of protein or metabolite identification and quantitation by mass spectrometry, and proficiency in MS bioinformatics software and analysis tools
- Expertise in developing, testing and deploying automated workflows in Nextflow, Galaxy or other workflow environment in Windows, Linux HPC or cloud computing environment
- Solid knowledge of informatics tools, statistical models and visualization/data mining packages (e.g. R/Shiny, genome visualization packages/browsers) and aptitude for adapting to complex new analysis packages and using them to their full potential
- First-hand experience in integrated analysis of large, complex proteomics and/or metabolomics datasets for biological insights, mechanisms of action, employing pathway analysis, modeling, machine learning and other approaches
- Familiar with machine learning, NoSQL, knowledge capture and other innovations in predictive analytics and data-driven discovery
- Demonstrated successful experience working on multiple projects to deliver complex interpretations to cross-functional teams
- Proven capacity to communicate effectively with technical and scientific colleagues alike, in formal presentations and small group meetings
- Excellent written and oral communication skills
- Demonstrated knowledge and understanding of the Life Sciences Healthcare industry and how it operates desirable
- Working knowledge with software tools such as MaxQuant, ProteomeDiscoverer and others for peptide/protein identification and quantitation, XC-MS for metabolite identification and quantitation
- Direct experience in the development and implementation of large-scale biological databases and related activities; along with experience developing rich visualizations from complex scientific data sets
- Experience with pathway and functional analysis tools such IPA, Pathway Studio, Cytoscape, GSEA, TMHMM and SignalP
- Proven track record of publishing relevant bioinformatics or systems biology results in peer-reviewed journals
- Demonstrated contributions in target discovery is desirable
- Demonstrated scientific knowledge of cell biology, molecular biology, or immunology, especially as it relates to biomedical research and development
- Direct laboratory experience and working with biologists to design and analyze experiments is advantageous.
Next Steps – Apply today!
To be considered for this exciting opportunity, please complete the full application on our website at your earliest convenience – it is the only way that our Recruiter and Hiring Manager can know that you feel well qualified for this opportunity. If you know someone who would be a great fit, please share this posting with them.
AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.
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.