Bioinformatics Data Scientist - Early Cardiovascular, Renal and Metabolism
Do you have expertise within Data Science, Bioinformatics and Machine Learning? Do you have a passion for data and its utilization to gain novel insights into the molecular basis of disease? Would you like to apply your expertise in a cross-functional role at a company that are following the science and turning creative ideas into life changing medicines? At AstraZeneca, we are harnessing data science & AI to help us achieve the next wave of breakthroughs – here we do things that have never been done before. Does this match your ambition and skills, then you might be the person we are looking for!
We are now offering exciting opportunities for talented and highly motivated individuals to join us as Bioinformatics Data Scientists at several different career levels, depending on your previous experience. Our early stage CVRM (Cardiovascular, Renal and Metabolism) Data Science team is dedicated to the development of innovative treatments for Cardiovascular, Renal and Metabolic diseases. In this position, you will utilize your skills and expertise in the analysis and interpretation of large biological datasets to support the CVRM therapy area and contribute to a new understanding of patients, disease, and pharmacological intervention that will ultimately lead to new medicines for unmet clinical need.
These positions can be based either at AstraZeneca’s dynamic R&D sites in Gothenburg, (Sweden) or Cambridge (UK).
What you’ll do
As a Bioinformatics Data Scientist in the Data Science team, you will work on projects involving the analysis and interpretation of large complex datasets of mixed datatypes in order to gain novel understanding of the molecular mechanisms underlying cardiovascular, renal and/or metabolic (CVRM) diseases. Insights gained enable the validation of existing drug targets and the identification of novel targets and biomarkers for disease modulation and patient stratification.
To be successful in this role, we believe that you should be a highly dynamic, communicative and motivated individual, with a strong desire to collaborate in a dynamic cross-disciplinary environment. You will be given the opportunity to work on a wide variety of projects relating to bioinformatics, bio-image analysis, data science, and machine learning/artificial intelligence with focus on their relevance to CVRM disease areas.
Main Duties and Responsibilities
As a Bioinformatics Data Scientist, you will apply bioinformatics, biostatistics, systems biology, bioimage analysis, data science and machine learning techniques to data generated from models and patients, to enable the discovery of new targets and biomarkers through the exploration of the molecular basis of disease. Cutting-edge techniques will be utilized to enable the generation of novel molecular signatures for patient segmentation, demonstration of target engagement and translation to clinical outcome. This work will be carried out in collaboration with the Translational Science & Experimental Medicine and Clinical Development departments.
This role also involves employing bioinformatics, data science and ML/AI techniques to investigate, integrate and interpret data from leading Omics and bio-imaging platforms. Collaboration with internal and external partners to utilize relevant big data sources including static and dynamic omics, clinical observations, patient metadata, real world evidence and literature mining is also a key part of this role. We also perform robust statistical analysis and exploration of clinical datasets to support the early clinical development of medicines.
Essential for the role
- Strong quantitative background with a Masters or PhD (preferred) in bioinformatics, systems biology, bioimage analysis, statistics, data science, or other quantitative sciences. To qualify for a senior position, at least five years experience as a lead analyst in projects involving the analysis and interpretation of large biological datasets, in an academic or industry setting, is also required.
- Molecular biology, genetics and relevant disease area knowledge.
- Proven experience utilizing computational, statistical and machine learning techniques for the manipulation, visualization and analysis of large complex datasets in a biological or drug discovery context.
- Experience analysing and interpreting data such as those arising from omics, biomarker, imaging and clinical data.
- Programming skills in R, Python or equivalent language and experience with Unix/Linux and shell scripting.
- Ability to search, read, understand, interpret, and contribute to scientific research articles with a biology, bioinformatics, data science or machine learning focus.
- Excellent consulting, communication, and presentation skills, especially in communicating statistical and bioinformatics concepts, in a cross-disciplinary environment, to non-experts in these domains.
- Ability to work efficiently both individually and as part of a team in a matrix environment in order to meet objectives in a timely manner.
- Excellent English, both spoken and written
Desired for the role
Proven experience in several of the following topics:
- Statistical data analysis with knowledge within of at least some of the following areas: experimental design, linear/nonlinear models, mixed effect models, exploratory biomarkers, diagnostic analyses, applied Bayesian statistics, data mining, multivariate data analysis, and statistical learning.
- Experience leading statistical analysis projects aligned to drug discovery.
- Understanding of the biological systems and signaling involved in any of these cardiometabolic diseases - HF, T2D, CKD or NASH.
- Statistical analysis and integration of genomics, transcriptomics, metabolomics & proteomics datasets along with medical imaging, clinical and phenotypic data.
- Bioinformatics techniques for sequence similarity searching, gene expression profile clustering, GO-term mapping, and SNP analysis.
- Biological image data analysis, both classical and utilizing ML methods.
- Familiarity developing image analysis solutions and algorithms with Fiji/ImageJ, Knime, MATLAB, or other appropriate tools and directly in Python, Java or equivalent language
- Application of machine learning and artificial intelligence techniques to omics and/or image data.
- Analysis of large datasets using techniques to ensure reproducibility.
- Understanding of the identification and progression of drug targets through drug discovery and clinical development.
So, what’s next?
Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you! Welcome with your application (CV and cover letter) no later than February 28, 2021.
For more information about the position please contact hiring manager Ian Henry email@example.com
We will review the applications continuously so please apply as soon as possible.
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.