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Senior AI Scientist – Knowledge Graph Analytics

Location Cambridge, England, United Kingdom Job ID R-126642 Date posted 12/01/2022

Senior AI Scientist – Knowledge Graph Analytics

Cambridge UK

Competitive Salary + Benefits  

Make a more meaningful impact to patients’ lives around the globe

Here you’ll have the chance to create a meaningful difference to patients’ lives. With science at its heart, this is the place where breakthroughs born in the lab become transformative medicines – for the world’s most sophisticated diseases.

Answer unmet medical needs by pioneering the next wave of science, focusing on outcomes and shaping the patient ecosystem. With our ground-breaking pipeline, the outlook is bright.

Be proud to be part of a place that has achieved so much, yet is still moving forward. There’s no better time to join our global, growing enterprise as we lead the way for healthcare and society.

Are you a curious AI/ML researcher seeking a role where your expertise can make an extraordinary impact? This is an opportunity to join a dynamic and enthusiastic environment, whilst delivering critical support to drug discovery projects.

Join a place built on innovation and creativity. We harness digital, data science & AI to fast-forward our research. Making sure work born in a lab can make a real difference. Every day, impacting patients’ lives across the world.

You’ll be part of the Data Sciences & Quantitative Biology department – a global, diverse and delivery focused department where we collaborate to support drug projects aiming to impact patients’ lives.

In partnership with our experimentalist colleagues and other data scientists, we provide computational analysis and solutions to enable and enhance output from our technical platforms driving our drug discovery efforts.

What you’ll do

You will work as part of a team focused on developing and delivering robust analytical approaches to deriving insights and predictions from knowledge graphs and other biomedical networks (e.g. prediction of candidate drug targets).

You will work closely with other colleagues with complementary skills and experience, both within and beyond our department, to maximise the quality and impact of your work.

We truly believe that everyone contributes with a unique set of competence. Your curiosity and passion for personal development combined with support from colleagues, mentors and leaders, will ensure you maximise your potential and contribution, building from your current skills, abilities and experience.

Recent examples of our scientific output

For recent published examples relating to our department’s work and these roles, see:

Essentials for the role

Our team is a highly collaborative group of scientists, working in a constantly evolving technical and scientific landscape. Therefore, you’ll have to be comfortable working at a fast pace, with a team-focused approach. You have superb communication skills and a proactive and delivery-focused approach.

You also have:

  • A PhD - or equivalent numbers of years of experience post-degree - in mathematics, statistics, engineering, physics, economics, computational sciences or a related quantitative field.

  • In-depth experience with data science and machine learning approaches relevant to network science (e.g. graph based neural networks, representational learning, reinforcement learning).

  • Specific experience in graph theory/network science

  • Familiarity with use of database systems (e.g. SQL, NoSQL, graph) in data science/ML applications

  • Advanced skills in Python and Git: Experience writing robust, scalable and reproducible code using Python being managed via Git

Desirable for the role

  • Experience with graph databases and formats (e.g. RDF/RDF*, Neo4J) and software libraries relevant to ML/network analysis (e.g. pandas, scikit-learn, tensorflow, pytorch, networkx)

  • Working with impactful computing and cloud environments

  • Experience in probabilistic (e.g. Bayesian learning) or causal reasoning approaches

  • Experience with MLOps - Familiarly with management of ML experiments using MLOps tools such as MLflow, and experience designing ML experiments following standard methodologies such as hyper-parameter optimisation.

  • Proven track record of publishing relevant predictive modelling results and tools in peer-reviewed journals, conferences, and other scientific proceedings.

  • Experience of delivering value in a dynamic, iteratively working team and via collaboration with other teams

Why AstraZeneca

There are many opportunities to develop yourself and your career. From our diverse portfolio and teamwork to our ground-breaking innovations – it’s a place for lifelong learning.

You'll be based in our Cambridge R&D Centre, opening in 2021. This is placed in the heart of Cambridge Biomedical Campus - an open, welcoming and vibrant centre that will encourage our team and our partners to push the boundaries of scientific innovation.

We offer competitive salaries and excellent benefits, such as extra paid Holiday, Private Medical Benefit, Cycle to Work and much, much more.

So, what’s next!

If your passion is science and you want to be part of a team that makes a bigger impact on patients’ lives, then there’s no better place to be.

We look forward to find out more about you – make sure you apply !

Where can I find out more?

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Cambridge Biomedical Campus


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.

10001252 D DAAS R&D BioPharmaceuticals

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Great culture, great work assignments, supportive management. Rotation opportunity within the company. They value inclusion and diversity.