Employer Active
Job Alert
You will be updated with latest job alerts via emailJob Alert
You will be updated with latest job alerts via emailThis role is based inBarcelona with an on-site commitment of three days a week. Fluency inEnglishis .
Introduction to the opportunity:
Are you passionate about creating artificial intelligence and machine learning systems for real-world science applications Does contributing to preventing modifying and even curing some of the worlds most complex diseases inspire you Would you like to work on developing an iterative drug discovery and development process while drawing on methods across various fields from active learning to optimisation and search What about advancing our understanding of biology streamlining research and development processes and leveraging a variety of data modalities Do you thrive working in a supportive inclusive environment where creativity collaboration across disciplines and lifelong learning towards innovative breakthroughs are encouraged If yes this opportunity may be for you.
Join our interdisciplinary Centre for Artificial Intelligence team working on the frontier of AI research for digital biology. Your work will support the next generation of medicines and vaccines at the intersection of AI biology and engineering. Your work will contribute to transforming the drug discovery and development value chain as we know it uncovering novel biological insights automating processes streamlining decisions and improving the overall pipeline across all therapeutic areas at AstraZeneca.
Accountabilities:
You will work efficiently in a team to deliver projects optimally researching developing and using the novel AI theories methodologies and algorithms with engineering best practices and standard processes for various biology chemistry and clinical applications.
You will be part of multifunctional teams to conceive design develop and conduct experiments to test hypotheses validate new approaches and compare the effectiveness of different AI/ML systems algorithms methods and tools for new applications to support the discovery design and optimisation of medicines with improved biological activity.
You will contribute to addressing challenges and opportunities in the drug discovery and development value chain processes and provide innovative solutions in fields such as deep learning representation learning reinforcement learning meta-learning active learning approaches applied to de novo molecule design protein engineering in-silico discovery structural biology computational biology translational sciences biomarker discovery clinical research clinical trials and many other areas.
You will develop machine learning models designed explicitly for analysing heterogeneous biological data while collaborating with biology researchers to run algorithmically designed wet lab experiments to inform future experimental directions.
You will remain at the forefront of AI/ML research by participating in journal clubs seminars mentoring and personal development initiatives and contributing to publications and academic and industry collaborations.
Essential Skills/Experience:
A PhD in machine learning statistics computer science mathematics physics or a related technical discipline with relevant fundamental research experience in artificial intelligence and machine learning OR an MSc with a few years of relevant experience in the research and development of artificial intelligence and machine learning approaches to life sciences applications.
Fundamental AI research and development experience with well-rounded hands-on ability to implement AI/ML techniques based on publications or developed entirely addition experience in applying rigorous scientific methodology to (i) identify and create ML techniques and the required data to train models (ii) develop machine learning model architectures and training algorithms (iii) analyse and fine tune experimental results to inform future experimental directions and (iv) implement and scale training and inference engineering frameworks and (v) validate hypotheses.
Theoretical understanding combined with a strong quantitative knowledge of algebra algorithms probability calculus and statistics hands-on experimentation analysis and AI/ML techniques visualisation.
Algorithmic development and programming experience in Python or other programming languages and machine learning toolkits especially deep learning (e.g. Pytorch TensorFlow etc.).
Experience in practical aspects of AI/ML foundations and model design such as improving experimentation and analysis of model efficiency quantisation conditional computation reducing bias or achieving explainability in complex models.
Ability to communicate and collaborate effectively with diverse individuals and functions reporting and presenting research findings and developments clearly and efficiently to other scientists engineers and domain experts from different disciplines.
Fundamental research with hands-on practical experience and theoretical knowledge of at least one of the following research areas - examples include but are not limited to - multi-agent systems logic causal inference Bayesian optimisation experimental design deep learning reinforcement learning non-convex optimisation Bayesian non-parametric natural language processing approximate inference control theory meta-learning category theory statistical mechanics information theory knowledge representation unsupervised supervised semi-supervised learning computational complexity search and optimisation artificial neural networks multi-scale modelling transfer learning mathematical optimisation and simulation planning and control modelling time series foundation models federated learning game theory statistical inference pattern recognition large language models probability theory probabilistic programming Bayesian statistics applied mathematics multimodality computational linguistics representation learning foundations of generative modelling computational geometry and geometric methods multi-modal deep learning information retrieval and/or related areas.
Desirable Skills/Experience:
Experience designing new AI/ML approaches to deriving insights from proprietary and external datasets to generate testable hypotheses using algorithmic mathematical computational and statistical methods combined with theoretical empirical or experimental research sciences approaches.
Fluent in Python R and/or Julia other programming languages including scientific packages and libraries (e.g. PyTorch TensorFlow Pandas NumPy Matplotlib).
Research experience demonstrated by journal and conference publications in prestigious venues (with at least one publication as a leading author). Examples include but are not limited to NeurIPS ICML ICLR and JMLR.
Practical ability to work on cloud computing environments like AWS GCP and Azure.
Domain knowledge of tools techniques methods software and approaches in one or more areas such as protein engineering microbiology structural biology molecular design biochemistry genomics genetics bioinformatics and molecular cellular and tissue biology.
Evidence of open-source projects patents personal portfolios products peer-reviewed publications or similar track records.
Why AstraZeneca
When we put unexpected teams in the same room we unleash bold thinking with the power to inspire life-changing -person work gives us the platform we need to connect work at pace and challenge perceptions. Thats why we work on average a minimum of three days per week from the office. But that doesnt mean were not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world. Join the team unlocking the power of what science can do. We are working towards treating preventing modifying and even curing some of the worlds most complex diseases. Here we have the potential to grow our pipeline and positively impact the lives of billions of patients around the world. We are committed to making a difference. We have built our business around our passion for science. Now we are fusing data and technology with the latest scientific innovations to achieve the next wave of breakthroughs.
Ready to make a difference
Apply now and join us in our mission to push the boundaries of science and deliver life-changing medicines!
Date Posted
12-sept-2025Closing Date
31-oct-2025AstraZeneca 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 authorization and employment eligibility verification requirements.
Required Experience:
Senior IC
Full-Time