Introduction IBM Research takes responsibility for technology and its role in society. Working in IBM Research means you'll join a team who invent what's next in computing, always choosing the big, urgent and mind-bending work that endures and shapes generations. Our passion for discovery, and excitement for defining the future of tech, is what builds our strong culture around solving problems for clients and seeing the real world impact that you can make. IBM's product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive. Your role and responsibilities IBM Research Europe (UK) is seeking outstanding students for a summer internship. Our lab focuses on using cutting-edge artificial intelligence (AI) and machine learning (ML) to advance scientific discovery processes in industries that have applications in urgent societal impact areas such as healthcare and life sciences. The IBM Research team is harnessing the potential of biomedical foundation models (BMFMs) to tap into diverse multi-modal data sources, including human genomics, transcriptomics, proteomics, small molecules, and biologics. By leveraging these rich datasets, researchers aim to drive and enhance critical tasks throughout the drug discovery process, such as identifying novel drug targets, understanding disease mechanisms, designing de-novo small molecules, and developing new biologics. During the internship you will work in small groups under the mentorship of experienced researchers, addressing problems at the forefront of artificial intelligence for healthcare and life sciences. Areas of research include, but not limited to, new architectures and algorithms for training, fine-tuning, and applying biomedical foundation models to multi-modal life sciences data (e.g., multi-omics) with the aim of accelerate drug discovery tasks (e.g., predicting patient drug response, identifying new drug targets, predicting treatment outcome). Job responsibilities may include identifying and defining research challenges, developing prototype solutions, designing experimental setups to test hypotheses, refining solutions, and communicating findings through patent applications and publications in top-tier conferences Required technical and professional expertise - Candidates must be enrolled in a Master's or a PhD program in computer science, mathematics, statistics, computational genomics, bioinformatics or related disciplines. - Strong programming skills in one or more widely used languages such as Python. - Demonstrated experience in solving analytical problems using rigorous and quantitative approaches. - Demonstrated experience in developing, training, and testing machine learning and AI models, such as deep neural networks. - Demonstrated knowledge and experience in the analysis of omics data, especially human genomics and transcriptomics. Preferred technical and professional experience - Experience with machine learning tools and frameworks such as PyTorch. - Demonstrated experience in developing, training, and testing generative models, such as LLMs or multi-modal foundation models. - Proven expertise in designing, training, and deploying AI solutions that leverage complex healthcare and life sciences data to accelerate drug discovery and inform personalized medicine.