Team background
The AI Strategy & Innovation team sits within R&D IT in AstraZeneca. It is the team underpinning the delivery of the Oncology Data Science AI Strategy 2024. This multi-million-dollar investment serves to provide immense value through utilization of AI across the entire R&D value chain, brining deeper insights, automation, and scale to the portfolio. This team is working on machine learning approaches to tackle difficult problems in drug discovery and clinical trial evaluation.

Project topics
In this summer intern, we are looking for highly motivated students to work on the following topics:
· Developing and implementing computer vision and multimodal models for analysis of 3D volumetric medical images and the accompanying tabular clinical trial data.
· Developing reinforcement learning models to mimic how radiologists analyse CT scans.
· Developing fusion computer vision models that can combine multiple images together.
· Developing models to predict molecule toxicities to different human organs.
You will join a diversified research team; one supervisor will be assigned to you to work on the topic of choice. The working language is English.

The goals of the internship
· Speed up oncology drug discovery
· Publish paper at top-tier machine learning conferences such as NeurIPS, ICML, ICLR, CVPR, AAAI, MICCAI.

Duration
Ideally 3-month full time, July, August and September. Can be flexible depending on your availability, but at least 2 months.

Ways of working
Either onsite in Shanghai or remote.

Requirements
· Currently pursuing a degree in Computer Science, Software Engineering, Machine Learning, Biomedical Engineering, or a related field.
· Able to communicate in English.
· Experience in reading research papers.
· Foundational knowledge of deep learning frameworks (e.g., TensorFlow, PyTorch).
· Experience with image processing techniques and analysis.
· Familiarity with three-dimensional medical imaging formats (e.g., DICOM, NifTI).
· Strong programming skills in Python.
· Excellent problem-solving abilities and attention to detail.