Research Scientist - World Models

Graphcore

ABOUT GRAPHCORE At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence. JOB SUMMARY As a Research Scientist at Graphcore, you will advance AI research at the intersection of visual generative modelling, multimodal learning, world models and hardware-aware machine learning. You will explore new model architectures, training methods and deployment strategies with applications in embodied AI, robotics and autonomous systems. Example research directions could include efficient video generation, diffusion and flow-based models, multimodal representation learning, world models for agents, or analysis of how emerging generative AI workloads influence future AI accelerators. This role sits at the interface between frontier model research and AI hardware. Specialised hardware has been a key driver of AI progress over the last decade, and we believe that hardware-aware AI algorithms and AI-aware hardware developments will continue to be critical to advancing this field. We are looking for researchers and engineers with the theoretical depth, practical judgement and implementation skills to turn ambitious ideas into rigorous experiments, publications and technical insights that influence the future of AI compute. THE TEAM Graphcore Research participates in both fundamental and applied research to characterise the computational requirements of machine intelligence and to demonstrate how hardware can drive the next generation of innovative AI models. We publish at leading AI/ML conferences, including NeurIPS, ICML and ICLR, as well as specialist workshops, and collaborate with other research teams and organisations across the world. We pride ourselves on being a supportive and collaborative team, where we organise around individual research interests and solve problems together. Our work spans efficient compute, model scaling, distributed training and inference, and AI models for multiple modalities and applications, including sequence- and graph-based data. We’re based across London, Cambridge and Bristol, with projects and discussions that involve all our locations. Perhaps the best way to get an idea of what we’re all about is to read one of our papers or an article on our blog. If you’re excited to work at the cutting edge of AI and want to help shape the hardware and software systems that drive the future of AI compute, we’d love to hear from you! RESPONSIBILITIES AND DUTIES * Develop and evaluate new ideas in visual generative AI, multimodal modelling and world models, from initial hypothesis through experiment design, implementation, analysis and publication. * Prepare, submit and present your work to AI conferences and workshops. * Work with researchers, software engineers and silicon teams to understand how emerging AI workloads can shape, and be shaped by, future Graphcore hardware and software systems. ABOUT YOU: Essential: * Master’s, PhD or equivalent experience in a technical discipline (e.g., Mathematics, Statistics, Computer Science, Physics, Chemistry, Biomedical Engineering). * Experience in visual generative AI, visual understanding or world models. * Strong Python programming skills using a modern deep learning framework, e.g. PyTorch or JAX. * Familiarity with deep learning fundamentals, including model architectures, optimisation, evaluation and scaling. * Ability to design, execute, analyse and clearly communicate ML experiments. * Mathematical foundations to support the above, including calculus, probability theory and linear algebra. * Evidence of research ability, such as conference or workshop submissions, publications, technical reports, open-source projects or impactful industrial research. Desirable: * Experience with multimodal reasoning or generation, action-conditioned models, embodied AI, robotics or autonomous systems. * Lower-level programming for hardware efficiency, e.g. C++/CUDA/Triton. * Practical familiarity with hardware considerations for deep learning, such as parallelism, memory hierarchy, vector and matrix engines, data movement, bandwidth limits and performance bottlenecks. * Practical familiarity with deep learning software stacks, such as graph compilation, kernel fusion, XLA/ATen operations, streams and asynchronous execution.   BENEFITS In addition to a competitive salary, Graphcore offers flexible working, a generous annual leave policy, private medical insurance and health cash plan, a dental plan, pension (matched up to 5%), life assurance and income protection. We have a generous parental leave policy and an employee assistance programme (which includes health, mental wellbeing, and bereavement support). We offer a range of healthy food and snacks at our central Bristol office and have our own barista bar! We welcome people of different backgrounds and experiences; we’re committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. Applicants for this position must hold the right to work in the UK. Unfortunately at this time, we are unable to provide visa sponsorship or support for visa applications

SpAItial

SpAItial is pioneering the next generation of World Models, pushing the boundaries of generative AI, computer vision, and the simulation of reality. We are moving beyond 2D pixels to build models that natively understand the physics and geometry of our world. Our mission is to redefine how industries, from robotics and AR/VR to gaming and cinema, generate and interact with physically-grounded 3D environments. We're looking for bold, innovative individuals driven by a passion for pushing the boundaries of generative 3D AI. You should thrive in an environment where creativity meets technical challenge and be fearless in tackling the hardest problems in 3D world modeling. Our team is built on a foundation of dedication and a shared commitment to excellence, so we value people who take immense pride in their work and place the collective goals of the team above personal ambition. As a part of SpAItial, you'll be at the forefront of building World Models that bridge generative AI and the physical world. If you're ready to make an impact, embrace the unknown, and collaborate with a talented group of visionaries, we want to hear from you. We're seeking a Research Scientist focused on 3D diffusion. You will lead research to design, build, train, evaluate, and optimize diffusion-based generative models that produce high-quality 3D content from images, video, and other inputs, with an emphasis on world-scale scenes that are spatially consistent and physically grounded. Responsibilities * Design and develop diffusion-based methods for 3D generation from images, video, and other inputs. * Build, train, optimize, and evaluate 3D diffusion models, including research on architectures, losses, and sampling strategies. * Apply and adapt cutting-edge image and video diffusion backbones (e.g., Stable Diffusion, FLUX, WAN, or comparable systems) to 3D generation. * Implement and experiment with state-of-the-art 3D representations including point clouds, meshes, and 3D Gaussian Splatting. * Develop training pipelines and loss functions that improve geometry accuracy, visual fidelity, and spatiotemporal consistency. * Collaborate with researchers to integrate physics-aware priors and world model capabilities into diffusion systems. * Analyze model performance, debug failure cases, and iterate rapidly to improve quality and robustness. Key Qualifications: * PhD in computer science, computer vision, graphics, machine learning, or a related field. * Top-tier publication record at venues such as CVPR, ECCV/ICCV, NeurIPS, and SIGGRAPH. * Strong fundamentals in deep learning and generative modeling, in particular diffusion models and large transformer models. * Hands-on experience training diffusion models and working with cutting-edge image and video model stacks (e.g., Stable Diffusion, FLUX, WAN, or similar). * Solid understanding of 3D processing concepts such as camera geometry, depth, reconstruction, point clouds, meshes, or Gaussian splats. * Proficiency in Python and deep learning frameworks such as PyTorch, with experience in large-scale model training and optimization. * Ability to implement research ideas, run rigorous experiments, and ship reliable ML code. At SpAItial, we are committed to creating a diverse and inclusive workplace. We welcome applications from people of all backgrounds, experiences, and perspectives. We are an equal opportunity employer and ensure all candidates are treated fairly throughout the recruitment process.

IMC

IMC is one of the world’s leading trading firms, combining quantitative research, technology and trading expertise to solve complex problems at scale. As Machine Learning becomes increasingly important within our Systematic Equities business, we are investing in frontier research that can shape the next generation of models, infrastructure and research capabilities. With access to world-class datasets, significant compute resources and a highly collaborative environment, IMC offers a unique opportunity to see cutting-edge research translated into real-world impact. We are seeking a Principal Research Scientist to help define and accelerate our long-term machine learning research agenda. Prior finance experience is not required. THE ROLE This role is designed for an established academic researcher or research scientist who wants to remain connected to the frontier of machine learning while applying their expertise in a highly impactful environment. You will work alongside quantitative researchers, engineers and research leadership to identify emerging research directions, evaluate new developments in machine learning, and help translate promising academic advances into practical applications. Rather than owning individual trading strategies, you will act as a scientific leader, mentor and advisor across the research organisation. You will also represent IMC externally through participation in leading conferences and engagement with the broader machine learning community. RESPONSIBILITIES * Shape the long-term machine learning research agenda within Systematic Equities. * Identify and translate advances from frontier ML research into practical opportunities. * Conduct original research and develop proof-of-concept solutions where appropriate. * Advise and mentor quantitative researchers on methodology, experimentation and research direction. * Help guide future investments in research tooling, infrastructure and compute capabilities. * Represent IMC within the global machine learning community through conferences such as NeurIPS, ICML and ICLR. * Contribute to publication efforts where appropriate and consistent with intellectual property considerations. SKILLS & EXPERIENCE * PhD in Machine Learning, Computer Science, Statistics, Mathematics, Physics or a related quantitative discipline. * Outstanding academic credentials and a strong publication record in leading research venues. * Current or recent experience in a faculty-equivalent academic or research leadership role such as Assistant Professor, Associate Professor, Professor, Group Leader, Principal Investigator, Senior Postdoctoral Researcher, or Senior Research Scientist. * Deep expertise in modern machine learning and strong awareness of emerging research trends. * Experience influencing research direction, mentoring researchers, or leading research initiatives. * Strong programming skills and experience with modern machine learning frameworks. * Excellent communication skills and the ability to collaborate across disciplines. WHAT WE OFFER * The opportunity to influence the future of machine learning at one of the world’s leading trading firms. * Access to exceptional datasets, infrastructure and large-scale compute resources. * Continued engagement with the academic community through conferences, collaborations and publication opportunities. * A collaborative environment where research can move rapidly from idea to impact. * Competitive compensation that reflects both scientific excellence and commercial impact. About Us IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.