Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 99 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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What Astrazeneca Pharmaceuticals Lp paid sponsored hires in similar roles10 certified filings for “Scientist, Cancer Immunology, Oncology Research” (Biochemists and Biophysicists) in MD: $104k–$138k, median $130k.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 99 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Astrazeneca Pharmaceuticals Lp paid sponsored hires in similar roles
- 10 certified filings for “Scientist, Cancer Immunology, Oncology Research” (Biochemists and Biophysicists) in MD: $104k–$138k, median $130k. Most were filed at wage level II (60%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
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-dev
Apply on employer site ↗