Senior Scientist, AI for Discovery — New Target Discovery

Posted 7 Days Ago
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Cambridge, Cambridgeshire, England, GBR
Hybrid
Senior level
Biotech • Pharmaceutical
The Role
Hands-on individual contributor applying AI and computational biology to new drug target discovery. Responsibilities include building multi-agent AI systems, predictive foundation models, virtual cell and perturbation models, production-quality scientific pipelines, and tools for therapeutic-area workflows. The role collaborates with biology and AI teams, communicates findings to varied audiences, and contributes to publications, conferences, and scientific partnerships.
Summary Generated by Built In
About AstraZeneca

At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to action, confident to lead, willing to collaborate, and curious about what science can do, then you're our kind of person.


We are a global, science-driven biopharmaceutical company dedicated to discovering, developing, and delivering innovative medicines that enrich the lives of patients. Our R&D engine combines deep biology expertise with cutting-edge artificial intelligence to accelerate how we find and validate new drug targets — ultimately bringing life-changing therapies to patients faster.


About Our Site

The Discovery Centre (DISC) is AstraZeneca’s global corporate headquarters and flagship research and development facility, located on the Cambridge Biomedical Campus in Cambridge, UK. The DISC brings together scientists, engineers, laboratory specialists, technology experts, and corporate colleagues in a highly collaborative environment. The facility provides a modern working environment with advanced laboratories and research infrastructure, including robotics, high-throughput screening, computational science, data-enabled research, and AI-supported technologies. Its location on the Cambridge Biomedical Campus provides access to a strong local network of healthcare, academic, and life-sciences expertise, supporting professional development, external collaboration, and scientific exchange across the biomedical sector.


About the Team

The AI for Discovery — New Target Discovery team exists to surface novel drug targets that Oncology and BioPharmaceuticals R&D can act on. We accelerate discovery by building and deploying two core AI capabilities: agentic AI and predictive models of biology to accelerate new target decision making across AZ R&D.


Our team supports both Oncology and BioPharmaceuticals therapeutic areas, sharing learnings across target discovery approaches and connecting new target strategy across AstraZeneca disease areas. We partner closely with therapeutic area scientists in Oncology, CVRM, Respiratory, Immunology, and Infectious Disease — as well as AI engineering and AI research teams.


What the Role Involves

This is a hands-on individual contributor role at the intersection of artificial intelligence and drug discovery biology. You will apply your technical skills in AI and biology to build, deploy, and evaluate agentic AI and predictive modeling tools that support new target discovery across AstraZeneca’s therapeutic areas.


Key responsibilities:

·       Work with therapeutic area scientists to understand their challenges and apply agentic AI and predictive models to accelerate target identification and validation.

·       Build and deploy multi-agent AI systems into therapeutic area workflows, translating AI capabilities into actionable scientific insights.

·       Develop, evaluate, and benchmark predictive foundation models for in silico biology — including perturbation prediction, virtual cell models, and preclinical efficacy forecasting.

·       Write production-quality code, pipelines, and tools that the team and broader organization can rely on.

·       Collaborate effectively within cross-functional project teams, communicating technical findings to both expert and non-expert audiences.

·       Contribute to AstraZeneca’s external visibility through publications, conference presentations, and scientific collaborations.


Essential Skills

·       PhD in computational biology, bioinformatics, AI/ML, systems biology, or a related quantitative discipline, or a Bachelor’s/Master’s degree with equivalent research experience. Candidates with additional post-doctoral or industry experience are equally encouraged to apply.

·       Experience with agentic AI, LLM-based reasoning systems, or multi-agent architectures applied to scientific problems.

·       Experience with predictive AI modeling for biology — foundation models, graph neural networks, perturbation models, or virtual cell approaches.

·       Understanding of drug discovery biology: target identification, target validation, mechanism of action, or translational science.

·       Strong technical proficiency in Python (required); experience building production-quality code, pipelines, and tools for scientific applications.

·       Hands-on experience with deep learning frameworks (PyTorch, JAX, or equivalent) for model development and evaluation.

·       Effective communication of technical and scientific findings to diverse audiences.

·       Enthusiasm and persistence in applying AI methods to complex biological problems.


Desirable Skills

·       Experience with multi-agent orchestration frameworks or scientific reasoning platforms.

·       Knowledge of targeted delivery modalities such as antibody-drug conjugates (ADCs), bispecifics, or degraders.

·       Experience integrating multimodal biological data (genomics, transcriptomics, proteomics, functional genomics).

·       Familiarity with clinical translation — biomarkers, patient stratification, or preclinical-to-clinical bridging.

·       Experience with cloud computing (AWS) and high-performance computing environments.

·       Proficiency in R for statistical analysis or bioinformatics workflows.

·       Experience working in pharma or biotech R&D.


Why AstraZeneca?

At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial — finding those moments and recognising their potential. Join us on our journey of building a new kind of organisation to reset expectations of what a bio-pharmaceutical company can be. This means we’re opening new ways to work, pioneering cutting edge methods and bringing unexpected teams together.


So, what’s next?

Are you already imagining yourself joining our team? Good, because we can’t wait to hear from you.


Where can I find out more?

Our Social Media,

Follow AstraZeneca on LinkedIn https://www.linkedin.com/company/1603/

Follow AstraZeneca on Facebook https://www.facebook.com/astrazenecacareers/

Follow AstraZeneca on Instagram https://www.instagram.com/astrazeneca_careers/?hl=en


When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.


#LI-HYBRID

Date Posted

22-Oct-2026

Closing Date

30-Oct-2026Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.

Skills Required

  • PhD in computational biology, bioinformatics, AI/ML, systems biology, or a related quantitative discipline, or a bachelor's/master's degree with equivalent research experience
  • Experience with agentic AI, LLM-based reasoning systems, or multi-agent architectures applied to scientific problems
  • Experience with predictive AI modeling for biology, including foundation models, graph neural networks, perturbation models, or virtual cell approaches
  • Understanding of drug discovery biology, including target identification, target validation, mechanism of action, or translational science
  • Strong proficiency in Python and experience building production-quality scientific code, pipelines, and tools
  • Hands-on experience with deep learning frameworks such as PyTorch or JAX
  • Ability to communicate technical and scientific findings to diverse audiences
  • Experience with multi-agent orchestration frameworks or scientific reasoning platforms
  • Knowledge of targeted delivery modalities such as antibody-drug conjugates, bispecifics, or degraders
  • Experience integrating multimodal biological data, including genomics, transcriptomics, proteomics, or functional genomics
  • Familiarity with clinical translation, biomarkers, patient stratification, or preclinical-to-clinical bridging
  • Experience with AWS and high-performance computing environments
  • Proficiency in R for statistical analysis or bioinformatics workflows
  • Experience working in pharma or biotech R&D

AstraZeneca Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AstraZeneca and has not been reviewed or approved by AstraZeneca.

  • Fair & Transparent Compensation — Pay is considered competitive across many roles when total rewards are factored in. Senior scientific and leadership bands are described with high ranges that reinforce competitiveness at upper levels.
  • Strong & Reliable Incentives — Bonuses, equity eligibility in many salaried roles, and solid sales on‑target earnings with upside are emphasized as meaningful parts of compensation. These elements boost overall value even where base pay is not the very highest.
  • Retirement Support — A 401(k) program with a strong company match and immediate vesting is repeatedly cited as a standout. Generous retirement support is viewed as enhancing the total package relative to peers.

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The Company
HQ: Gaithersburg, MD
70,000 Employees
Year Founded: 1999

What We Do

We're transforming the future of healthcare by unlocking the power of what science can do for people, society and the planet.

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