Jobs / United States / Astrazeneca Pharmaceuticals Lp
Associate Director, AI for Oncology Clinical Development
Astrazeneca Pharmaceuticals Lp · 🇺🇸 US - Cambridge Kendall SQ - MA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- 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. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- 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. 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 roles15 certified filings for “Associate Director Oncology Outcomes Research” (Medical Scientists, Except Epidemiologists) in MD: $126k–$185k, median $140k. Most were filed at wage level II (47%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
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).
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Sponsor Radar — Astrazeneca Pharmaceuticals Lp
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. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Astrazeneca Pharmaceuticals Lp →
About the role
Drug discovery has benefitted enormously in the current AI era yet comprises only a portion of the journey to bring new treatments to those in need. The final step – clinical drug development – is oft overlooked, despite requiring a significant proportion of time and investment. In the AI for Clinical Development team at AstraZeneca, we're reimagining the process of clinical development. Our vision is to bring safe, efficacious treatments to patients in a way that quantifiably improves our chance to do this faster, more cost-effectively, and with reduced patient burden. In this role, you will be a technical lead to help us leverage the power of AI to the fullest, alongside our other computational, statistical, and machine learning tools. You will work across the enterprise to define and deliver on AstraZeneca’s most pressing clinical development questions. You will proactively collaborate in cross-functional teams spanning AstraZeneca’s key Oncology foci of hematology, cell therapy, antibody-drug conjugates, small molecules, and biologics. This is an unprecedented, high visibility opportunity to invent new ways to leverage data, models, and learnings across the spectrum of cancer biology and drug modalities – and importantly, you and the team will apply these new methods to measurably advance the late-stage drug pipeline and our group’s ambition. Responsibilities: • Contribute to the AI strategy and roadmap for Oncology early and late phase clinical development • Serve as a key technical lead and contributor in matrixed teams to deliver complex, high-stakes AI projects • Evaluate and develop cutting-edge AI methods in one or more areas of problem definition, data considerations, governance, algorithm development, validation, and adoption • Partner with clinical development, biometrics, regulatory, and study teams to develop and then validate novel AI solutions into clinical study design, execution, strategy, and decision-making • Establish and maintain external collaborations with academic institutions, technology partners, and industry consortia to access novel capabilities and advance the AI roadmap • Represent AstraZeneca at scientific conferences, standards bodies, and peer-reviewed venues; contribute first- or last-author publications in leading ML and clinical AI journals • Mentor and support peers within the team Qualifications: • PhD in a quantitative discipline such as computer science, bioinformatics, computational biology, mathematics, physics, biophysics, computational neuroscience, biostatistics • At least 2+ years’ work experience outside of PhD with measurable impact (e.g. models delivered, patents, SaMD filings, first-author publications, open-source projects, standards-body participation) Technical requirements: • Exceptional software development and coding skills, leveraging frontier coding agent frameworks; knowledge of computing hardware a plus • Deep experience, knowledge, and understanding of one or more fields of biology • Deep understanding of machine learning fundamentals, with domain expertise in one or more of the following - • Training and tuning foundation models • Bayesian inference • Temporal modeling • Multimodal integration and modeling • Model calibration and domain adaptation • Data-centric AI: acquiring, creating, and curating datasets for model training / post-training / benchmarking / evals • Model and data evaluations and benchmarking • Model interpretability • Model post-training and alignment Preferred Skills: • Deep expertise in cancer biology • Experience working with biological data such as molecular (e.g. DNA, RNA, protein), imaging (radiology, microscopy), or clinical text (e.g. EHR, clinical notes) • Experience in drug development