**Introduction** At IBM, work is more than a job - it's a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better, but to attempt things you've never thought possible. Are you ready to lead in this new era of technology and solve some of the world's most challenging problems? If so, lets talk. **Your role and responsibilities** We seek applications from innovative researchers with expertise in machine learning and artificial intelligence to join our Sustainable Materials team. You will tackle challenges at the forefront of AI, advancing generative and multi-modal models for high-impact applications in materials discovery and sustainability. Your Role and Responsibilities: 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 sectors. * Enhancing foundation models for applications in materials discovery, and chemistry, with the goal of solving real sustainability challenges. * Designing and testing single or multi-agent AI systems using cutting-edge benchmarks, or developing solutions tailored to business-critical use cases. As part of the role, you will need to be comfortable with identifying and defining research challenges, prototyping solutions, designing experimental setups to test certain hypotheses, refining solutions, and communicating findings through patent applications and publications in top-tier conferences. 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 above. **Required technical and professional expertise** * Doctorate Degree in Computer Science (Artificial Intelligence), Computational Materials Science, Climate science, Physics, Mathematics, or closely related field. * Experience in machine learning, building workflows and AI models in platforms such as Pytorch, TensorFlow, Ray, etc. * Strong AI skills in transfer learning, model distillation, surrogate models, reinforcement learning, ideally with NLP applications. * Research experience in designing and developing domain-specific or/and generalisable models. * Demonstrated experience in developing, training, and testing deep neural networks. **Preferred technical and professional experience** * Strong research skills in natural language processing (NLP) * Demonstrated experience in developing, training, and testing generative models, such as LLMs or multi-modal foundation models. * Being able to communicate research ideas clearly and effectively by demonstrated publications and presentations at top-tier AI conferences such as NeurIPs, ICLR, ICML, ACL, EMNLP, CVPR etc. * Experience with machine learning and deep learning techniques for knowledge base and graphs construction in materials domain. * Research experience in building and operationalizing AI-based surrogate models for (complex) materials / molecules.