Associate Principal Scientist Bioinformatics
Do you have expertise within Biostatistics and Bioinformatics? Would you like to apply your expertise in a cross-functional role at a company that are following the science and turn ideas into life changing medicines? Then you might be the one we are looking for!
We are now looking for an Associate Principal Scientist Bioinformatics to join the Translational Science department within the Cardiovascular Renal and Metabolic Diseases (CVRM) therapeutic area at AstraZeneca in Gothenburg for a temporary position for 8 months.
CVRM is one of the three main therapeutic research areas within Innovative Medicines and Early Development (IMED), AstraZeneca´s small molecule biotech unit that deliver candidate drugs into late-stage clinical development. CVRM is based in AstraZeneca´s world-class vibrant R&D center, located in Gothenburg, Sweden. CVRM Translational Sciences has the remit to bridge pre-clinical, early and late drug development by providing early target validation in human and by driving precision medicine approaches through biomarker science. The Bioinformatics team within Translational science works within cross-disciplinary drug project teams throughout the discovery and translational pipeline driving new target discovery, pre-clinical and clinical research.
As an Associate Principal Scientist Bioinformatics you will be part of a team that is advancing precision medicine concepts, driving a new generation of CVRM targets and validating existing portfolio targets. You will play a key role in supporting pre-clinical and early clinical projects or patient studies to drive human target validation, experimental models evaluation and biomarkers discovery. You will work closely with your peers who are experts in cardiometabolic and renal disease biology, genetics, systems biology and machine learning.
Main Duties and Responsibilities
- Deliver robust bioinformatics data package to support portfolio projects progression, new targets and biomarkers discovery across all CVRM research areas. Make key contributions to the TS project plans, collaborations and scientific strategies.
- Work closely with TS members and fellow CVRM discipline leaders and teams to leverage computational/ statistical methodologies, contribute to experiment/study designs, write and implement the data analysis plan, and interpret analysis results.
- Ensuring access and deployment of state-of-the-art bioinformatics, systems biology methods and modalities towards furthering CVRM bioinformatics strategy.
- Collaborate with bioinformatics, biostatistics and biology experts across different functional units within AstraZeneca to leverage best practices in trans-omics molecular, clinical and phenotypic data analysis and integration.
- Design and apply innovative computational/statistical/machine learning approaches and data visualizations techniques to:
-Identify and characterize CVRM disease drivers, molecular targets, mechanisms and biomarker hypotheses.
- Generate actionable biological insight from genomic data.
- Link multi-omics data sets from patients and in vitro/vivo models with relevant clinical datasets and biomarkers (when applicable).
- Relevant PhD (or equivalent graduate degree plus experience) in bioinformatics, systems/computational biology, statistics, biostatistics, computer science, mathematics, or a related field, plus between 3 and 5 years post-doctoral or industrial experience.
- Proficiency in analyzing and interpreting data from multiple omic platforms in association with clinical and phenotypic datasets.
- Deep expertise in bioinformatics, systems biology or computational biology, and knowledge of at least the following areas: network/pathway analysis, multi-omics integration, genomics, proteomics, metabolomics, exploratory biomarker, diagnostic analyses, statistical genetics,
- Broad expertise in biostatistics, multivariate data analysis and statistical learning.
- Programming proficiency and experience with
- Statistical and computational: R, SAS, JMP, Spotfire, and Matlab.
- Programming environment: Unix/Linux
- Programming languages: Python, Perl
- Bioinformatics: Bioconductor, IPA
- Database management systems
- Demonstrated effectiveness working on a multidisciplinary team to achieve team objectives.
- Excellent consulting, communication, and presentation skills, especially in communicating statistical and bioinformatics concepts to non-experts in these domains.
- Good project management and matrix leadership skills. Ability to collaborate well with non-statistical functions.
- An excellent publication track record in the field.
- Excellent English, both spoken and written
- Working knowledge of genetics/genomics and computational biology.
- Experience of leading bioinformatics efforts aligned to drug discovery.
- Understanding of the biological systems and signaling involved in any of these cardiometabolic diseases - HF, T2D, CKD or NASH.
- Experience using data science techniques for:
- Time series and real-time data analytics
- Real world evidence/electronic health records
- Predictive machine/deep learning, with a focus on techniques revealing actionable biological insight from feature use and predictive rules.
- Mathematical, Boolean and/or computational modeling of human disease mechanisms.
- Graph and Network Biology techniques.
Dela detta jobb