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AstraZeneca

AI Research Scientist

AstraZeneca is hiring an AI Research Scientist. It pays $125k-$187k a year and Level rates it ; you can apply on AstraZeneca.

Level's read on this job

  • On Level's scale, this research scientist role is Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include AI research.
  • Level lists 1,100+ other open roles at AstraZeneca.
  • The role was posted in the last few days.

AI in this role

ai-research
Senior Scientist, AI for Oncology Clinical Development

Locations: Cambridge, USA (3 days in office, 2 days remote)


Join AstraZeneca: Where AI Meets Life-Changing Impact

What if your AI research could help transform not only how medicines are discovered, but how they reach patients?


Drug discovery has benefited enormously from advances in artificial intelligence. Yet clinical development, one of the most consequential stages in bringing new treatments to patients, remains an extraordinary opportunity for innovation.


Within AstraZeneca’s AI for Clinical Development team, we are reimagining that journey. Our ambition is to use AI, machine learning, statistics, and computational science to help bring safe and effective treatments to patients faster, more efficiently, and with less burden on those participating in clinical research.


We are looking for a Senior Scientist, AI for Oncology Clinical Development who can combine outstanding machine learning expertise with the curiosity and drive to solve complex, high-impact scientific problems.


What you’ll do


As a technical contributor, you will work in cross-functional, matrixed teams to address some of AstraZeneca’s most important clinical development questions.


You will have the opportunity to:


  • Lead the technical delivery of complex, high-stakes AI initiatives.
  • Evaluate and develop advanced AI methods across problem definition, data strategy, governance, algorithm development, validation, and adoption.
  • Create and validate novel AI solutions for clinical study design, execution, strategy, and decision-making.
  • Apply data, models, and insights across cancer biology and multiple drug modalities.
  • Collaborate across key Oncology areas, including hematology, cell therapy, antibody-drug conjugates, small molecules, and biologics.
  • Build external collaborations with academic institutions, technology partners, and industry consortia.
  • Represent AstraZeneca at scientific conferences, standards bodies, and peer-reviewed venues.
  • Contribute first-author research to leading machine learning and clinical AI journals.
  • Help shape and share technical knowledge, standards, and effective practices across the team.

This is an opportunity to invent new approaches and then see them applied to real clinical-development challenges, with the potential to measurably advance AstraZeneca’s late-stage Oncology pipeline.


Essential experience


You will have:

  • A PhD in a quantitative discipline such as computer science, mathematics, physics, biophysics, bioinformatics, computational biology, computational neuroscience, or biostatistics.
  • Exceptional software-development and coding skills, including experience using frontier coding-agent frameworks.
  • A deep understanding of machine learning fundamentals.
  • Strong expertise in one or more of the following areas: Training and tuning foundation models Bayesian inference Temporal modelling Reinforcement learning Multimodal integration and modelling Model calibration and domain adaptation Data-centric AI, including dataset creation, curation, post-training, benchmarking, and evaluation Model and data evaluation Model interpretability Model post-training and alignment Multi-agent systems and agent harnesses

Desirable experience


Your application will be strengthened by experience in one or more of the following:

  • Biology or biomedical research.
  • Applying machine learning to molecular data, including DNA, RNA, or proteins.
  • Working with imaging data such as radiology or microscopy.
  • Working with clinical text, electronic health records, or clinical notes.
  • Clinical trial design, biomarker discovery, companion diagnostics, dosing, safety, endpoints, or regulatory science.
  • Delivering models, patents, software-as-a-medical-device filings, first-author publications, open-source projects, or standards-body contributions.
  • Maintaining strong connections with the wider machine learning research community.
  • Working effectively across global, matrixed organizations, sites, and therapy areas.
  • Using agentic tools to augment rigorous scientific and technical work.
  • Assessing emerging AI research and distinguishing meaningful advances from hype.

Why join us?


This is not AI research at arm’s length from its application. You will work alongside scientists, clinicians, statisticians, and technologists on difficult problems where robust technical innovation can support meaningful clinical decisions.


You will join an environment that combines world-class science with cutting-edge technology, encourages collaboration across disciplines, and applies AI where it can make a tangible difference for patients. AstraZeneca’s Enterprise AI messaging emphasizes real-world impact, complex problems, scientific and technological collaboration, and autonomy to innovate within responsible frameworks.


In Oncology, you will contribute in an interdisciplinary setting where AI, novel biomarkers, endpoints, and innovative trial designs can create new possibilities for clinical development.


Bring your expertise. Challenge established approaches. Help shape how AI advances Oncology clinical development.


Ready to make an impact?

If you are motivated by technically ambitious AI research and want to see your work applied to some of the most important challenges in Oncology, we would welcome your application.


Join AstraZeneca, where AI meets life-changing impact.

The annual base pay for this position ranges from $124,713.60 - $187,070.40 annually. Our positions offer eligibility for various incentives—an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.

Date Posted

03-nov-2026

Closing Date

16-nov-2026

Our 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.

How we rate this

AI Research Scientist at AstraZeneca rates 97 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI Research

Also common in research scientist jobs at this level

Pay

This job starts at
$125k
Typical research scientist job
$192k

This posting starts 35% below the typical research scientist job. See research scientist jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: AI Research. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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