Associate Director, AI for Discovery — New Target Discovery
$144.65k - $216.97kAssociate Director, AI for Discovery — New Target Discovery
Location: Cambridge, MA US (Kendall Square)
Salary: Competitive + Excellent Benefits
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
Our Cambridge, MA site at 290 Binney Street in Kendall Square is a 570,000-square-foot, state-of-the-art facility that consolidates approximately 1,500 R&D, commercial, and corporate employees. Positioned within the world’s leading life sciences and biotech innovation cluster, the site is designed to foster deep collaboration with neighboring academic institutions, healthcare networks, and biotech partners. The facility features advanced laboratory infrastructure, a dedicated conferencing center, and a high-performance workplace designed to balance natural daylight, collaboration, and employee comfort.
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 an expert, hands-on role at the intersection of artificial intelligence and drug discovery biology. You will bring deep technical expertise in AI and biology to drive the adoption and application of agentic AI and predictive modeling tools across AstraZeneca’s therapeutic areas to accelerate new target discovery.
Key Responsibilities
- Partner with therapeutic area scientists to identify high-impact use cases where agentic AI and predictive models can accelerate target identification and validation.
- Apply technical expertise to deploy multi-agent AI systems into therapeutic area workflows, translating cutting-edge AI capabilities into actionable scientific insights.
- Advise cross-functional matrix project teams on leveraging AI-driven approaches for target prioritization and investment decisions.
- Contribute to the development and benchmarking of predictive foundation models for in silico biology — including perturbation prediction, virtual cell models, and preclinical efficacy forecasting.
- Contribute to the team’s scientific strategy and roadmap in close partnership with the Senior Director and team members.
- Build AstraZeneca’s external visibility through publications, conference presentations, and scientific collaborations.
- Act autonomously as a subject matter expert, influence through technical credibility, and drive outcomes across organizational boundaries.
Essential Skills
- PhD in computational biology, bioinformatics, AI/ML, systems biology, or a related quantitative discipline, with 5+ years of post-doctoral and/or industry experience.
- Demonstrated expertise in 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.
- Deep 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.
- Ability to influence cross-functional teams as a technical expert and strategic contributor.
- Strong scientific communication — track record of publications, conference presentations, or external collaborations.
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
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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.
The annual base pay for this position ranges from $144,649 - $216,973 USD Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.
In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program. Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans.
Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base pay (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.
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Date Posted
22-Sept-2026Closing Date
06-Oct-2026Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.
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