Must be enrolled in a MSc/PhD program in Biomedical Engineering, Statistics, Mathematics, Data Science, Electrical Engineering, Computer Science or related field; PhD candidate preferred.
In-depth knowledge of machine learning and deep learning, with a focus on imaging data, especially biomedical imaging.
Experience with omic data analysis, large language model (LLM), multimodal analysis or Generative Adversarial Network (GAN) is advantageous.
Proficiency in parallelization, HPC cluster computing, Python, deep learning frameworks, and reproducible research practices (like Git).
Strong communication and collaboration skills, coupled with a passion for applying machine learning to healthcare.
Preferred experience includes publications in top conferences/journals and contributions to open source projects.
Responsibilities:
Collaborate with the team and other stakeholders to evaluate state-of-the-art computer vision techniques and applications in pathology image analysis, particularly with deep-learning and machine-learning approaches
Devise, implement and interpret deep learning algorithms to address selected research questions in digital pathology
Proactively share findings and knowledge to support the development of the wider Roche community
Help shape the direction of machine learning and artificial intelligence within Roche.