IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, discovering how blockchain will reshape the enterprise, and much more. Join a team that is dedicated to applying science to some of today's most complex challenges, whether it’s discovering a new way for doctors to help patients, teaming with environmentalists to clean up our waterways or enabling retailers to personalize customer service.
The work location for this role is the IBM Hursley Lab near Winchester or the Daresbury Lab near Warrington. IBM has a hybrid work model with 3 days onsite expected.
We seek applications from innovative researchers with machine learning and artificial intelligence expertise to join our Climate and Sustainability and our Sustainable Materials team. You will tackle challenges at the forefront of AI, advancing generative and multi-modal model AI for high-impact materials discovery, geospatial and climate-related applications. We seek creative, driven individuals who are comfortable tackling ambiguous challenges, eager to push the limits of what's possible, and committed to shaping the future of AI and sustainability. Applicants should submit a CV and a one-page cover letter that highlights your experience and passion for the research themes outlined below.
As a member of our IBM Research team, you will explore novel research opportunities by addressing problems at the forefront of AI. Potential research topics include, but are not limited to:
- Developing advanced AI architectures and algorithms to train, fine-tune, and apply generative models for multi-modal tasks, directly influencing high-impact industry sectors.
- Enhancing foundation models to solve real sustainability challenges, including specialised foundation models for domain applications as well as enhancing capabilities of general language models.
- Design and test single- or multi-agent AI systems using cutting-edge benchmarks or develop solutions tailored to business-critical use cases.
As part of the role, you must be comfortable identifying and defining research challenges, prototyping solutions, designing experimental conditions to test hypotheses, refining solutions, and communicating findings through patent applications and publications in top-tier conferences.
- Doctorate Degree in Computer Science (especially in Artificial Intelligence focusing on computer vision, LLMs, NLP, data. generation), Physics, Mathematics, or a closely related field.
- Demonstrated experience in benchmarking foundational models for real-world applications.
- Experience in machine learning and developing AI models in frameworks such as Pytorch, TensorFlow, FSDP, Ray, and so forth.
- Expertise in one or more AI areas, including transfer learning, model distillation, surrogate models, and reinforcement learning.
- Research experience in designing and developing domain-specific and/or generalisable models.
- Strong research skills in large AI models for materials, geospatial and climate applications.
- Demonstrated experience in developing, training, and testing generative models, such as LLMs or multi-modal foundation models.
- Demonstrated ability to communicate research through publications or presentations in top-tier conferences such as NeurIPs, ICLR, AAAI, AGU, IGARSS.