Senior Data Scientist - Machine Learning & AI in Genomics
Location: Barcelona, Spain
Competitive Salary & Benefits
Meaningful Impact: Make a more meaningful contribution to patients' lives every day.
Make a more meaningful impact in your career, with greater ownership and accountability to make a contribution. We're looking for people driven by making a difference to patients and society, dedicated to doing the right thing.
Be part of the team where you are empowered to follow the science
Join the team that follows the science unlike anywhere else. This is the place for curious minds. Dig deep into the biology of complex disease and uncover breakthroughs.
Our belief powers us to push the boundaries. As we improve success rates, we keep moving forward, celebrating both successes and failures along the way.
What you'll do
We have an opportunity for a talented Senior Data Scientist at the Centre for Genomics Research (CGR) to be part of ground-breaking research at the forefront of human genomics. You will be part of a dynamic team in CGR's multidisciplinary genomics research environment comprising bioinformaticians, computational biologists, genome scientists, software engineers, postdoctoral researchers, and disease area specialists. You will also work closely with specialists in translational science, drug discovery, pre-clinical modelling, and clinical development. In this role, you will be responsible for designing and implementing novel machine learning and deep learning methods applied to genomics.
Design and implement novel machine learning and deep learning methods for variant interpretation and other genomics research questions.
Extract research and/or business value from highly unstructured genomic data and metadata, including the 500,000 UK Biobank resource.
Work with engineering and architecture to support large scale data preparation, the optimisation of analytics platforms, and the industrialisation of proven analytics methods.
Coordinate and execute analyses within AstraZeneca's Centre for Genomics Research.
Deliver novel insights into the biology of disease, including complex diseases but also extending to rare diseases.
Develop methods for validation of new targets for medicines and the improvement of selection of patients for clinical trials.
Assess the scientific & technical integrity of algorithms and tools within the analysis pipeline.
Maintain a well-developed knowledge of genomic science and technical advances in the international community.
Present novel results to top tier genetics and/or machine learning conferences and publish in high impact journals.
Collaborate to apply genomic analysis with discovery and development teams.
Communicate results to a variety of audiences, technical and non-technical.
Ensure own work, and work of team, is compliant with Good Laboratory Practice, Safety, Health and Environment standards and all other internal AstraZeneca standards and external regulations.
Essential Criteria
PhD degree (or equivalent experience) in Computational Biology, Bioinformatics, Machine Learning, or a related quantitative discipline.
Solid experience in developing learning methodologies and building robust production machine learning systems.
Strong programming skills and knowledge of algorithms and data structures.
Solid experience in one or more languages (Python, R, C++) and in open-source ML packages (e.g. scikit-learn, PyTorch, TensorFlow, Keras).
Applied experience with deep learning models (such as CNNs and Transformers).
Ability to communicate effectively with team members and non-experts, both verbally and through documentation.
High level understanding or interest in the potential of genomics to impact drug discovery.
Ability to prioritize and problem-solve.
Excellent interpersonal skills and willingness to work within a team in a quickly evolving environment.
Track record of peer-reviewed publications in high-level scientific journals.
Passion for applying machine learning to the life sciences domain.
Desirable Criteria
Experience in large-scale data analysis in genomics and/or other omics.
Experience with Knowledge Graphs and Graph Neural Networks.
Familiarity with Generative AI (LLMs).
Experience in Unix environments and Bash scripting.
Experience in high performance and/or cloud computing.
Why we love it
If your passion is science and you want to become part of a team that makes a bigger impact on patients' lives, then there's no better place to be. Here we truly understand science and apply it every day to strengthen and grow our pipeline!
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