Thesis work, 30 credits - Accelerating Early Cost-Effectiveness Modelling with GenAI

AstraZeneca; Oslo; On-site; NOK 600,000 - 800,000; Full time

Job summary

A global biopharmaceutical company in Oslo is inviting Master’s students to apply for a thesis project focused on using generative AI to enhance cost-effectiveness modeling for oncology drugs. This role involves collaboration with a health technology assessment team and aims to generate early estimates that streamline planning for future treatments. Applicants should be enrolled in a related Master's program and proficient in English.

Qualifications

• Enrolled in a Master's program with modules in health economic modeling or evaluation.
• Fluent in English.

Responsibilities

• Collaborate with the Nordic HTA team on cost-effectiveness modeling.
• Optimize prompt engineering to develop cost-effectiveness models.
• Generate early cost-effectiveness estimates using internal data.

Skills

Health Economics

Prompt Engineering

English proficiency

Education

Master's program in Health Economics or similar

Job description

Overview

Are you passionate about applying advanced technologies to real-world healthcare challenges? AstraZeneca’s marketing company in Oslo invites master’s students to apply for a thesis project using generative AI to evolve cost-effectiveness modelling for drugs in AstraZeneca’s oncology pipeline.

About AstraZeneca

AstraZeneca is a global, science-led, patient-centred biopharmaceutical company focusing on discovering, developing, and commercialising prescription medicines for some of the world’s most serious diseases. Beyond being a global leading pharmaceutical company, at AstraZeneca we\'re dedicated to being a Great Place to Work and empowering employees to push the boundaries of science and fuel their entrepreneurial spirit.

Thesis work description

Collaborate with our highly experienced Nordic health technology assessment (HTA) team, leveraging AstraZeneca’s in house portfolio of large language models. You will optimise prompt engineering to develop early cost-effectiveness model based on internal planning materials—such as clinical trial protocols—to identify, extract, and analyse relevant data.

The goal

Generate early cost-effectiveness estimates for future oncology indications and compare GenAI-driven outputs against current manual modeling practices to assess efficiency and quality. Your work will help refine processes that inform critical internal planning and future investment decisions in new medicines.

Your impact

You will contribute directly to improving the efficiency and accuracy of cost-effectiveness analysis for future oncology indications, supporting AstraZeneca\'s mission to deliver patient value and innovative therapeutics. Your findings will influence how the potential value of new medicines are assessed, potentially streamlining planning and expediting time-to-value for future treatments.

Structure

• Duration: Spring term 2026
• Credits: 30

Essential Requirements

• Enrolled in a Master\'s program within Health Economics or similar, having taken previous modules in health economic modelling or economic evaluation.
• Excellent in English

So, what’s next?

Apply today and take the chance to be part of making a difference, making connections, and gaining the tools and experience to open doors and fulfil your potential. We can\'t wait to hear from you!

We welcome your application as soon as possible, but ahead of the scheduled closing date 19th of October 2025. In the event that we identify suitable candidates ahead of the scheduled closing date, we reserve the right to withdraw the vacancy earlier than published.

Date posted

Date Posted 24-Sep-2025

Closing date

Closing Date 19-Oct-2025

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.