4 of 4 Research Scientist Jobs in Cambridgeshire

Permanent Role Location : Cambridge Hybrid Policy: 3 days onsite and 2 days working from home weekly Role and Responsibilities As anAI Research Scientist, you will be part of a dynamic team working on next-generation machine learning technologies for real-world deployment on consumer devices. Your role will involve: Driving research and development in areas such as … on-device large language and vision-language models (LLMs/VLMs), adaptive inference, and efficient mobile ML systems. Contributing to both ongoing research agendas and helping define new directions that push the boundaries of AI on edge devices. Collaborating closely with cross-functional teams across research and product engineering to transition ML innovations from prototypes into production. Designing … eager to develop innovative AI systems that will have real-world impact. Skills and Qualifications Education & Experience: PhD in Computer Science, Electrical Engineering, or a related field; or equivalent research experience in industry or academia. Open to applicants across a range of seniority levels with relevant expertise. Core Skills: Proficiency with ML frameworks such as PyTorch, TensorFlow, or JAX. More ❯

systems, with the overarching objective to deliver state-of-the-art efficient AI models across Samsung consumer devices. To this end, we focus on high-impact projects that balance research and commercial outcomes. Our group conducts research on on-device and edge-based ML systems, focusing on model/system and hardware/software co-design, adaptive inference … systems, with the overarching objective to deliver state-of-the-art efficient AI models across Samsung consumer devices. To this end, we focus on high-impact projects that balance research and commercial outcomes. Our group conducts research on on-device and edge-based ML systems, focusing on model/system and hardware/software co-design, adaptive inference … is characterized by its diverse backgrounds and expertise, ranging from pure machine learning and mobile/embedded systems to computer architecture and robotics, with strong emphasis on combining excellent research skills with hands-on development abilities. This diversity has enabled us to develop groundbreaking cross-stack ML systems and algorithms. Throughout our projects, we maintain strong ties with close More ❯

We are seeking a Research Scientist for our quantum algorithms team in London or Cambridge, UK. Key responsibilities Conduct research on new computational models and techniques to reduce the circuit depth of quantum algorithms. Develop and implement novel quantum algorithms integrated with early fault-tolerant protocols and error correction or detection primitives. Contribute to end-to-end … resource estimation of quantum algorithms under realistic hardware constraints. Communicate scientific results internally across teams and externally through publications and conference presentations. This is a permanent research position typically requiring a PhD in a relevant field. Our team members regularly publish scientific papers and present their results at leading conferences. Full details and application: This question is for testing More ❯

We wish to appoint a Research Assistant or Postdoctoral Research Associate with experience in Electronic Health Records (EHR) research to work alongside the University Department of Psychiatry, clinical institutions such as Cambridgeshire and Peterborough NHS Foundation Trust, and with a secondment to industry (Akrivia Health) to advance science and develop common data models for electronic health records … people with mental disorders, under the guidance of Dr Osimo and Prof Murray at Cambridge, and a line manager to be selected at Akrivia Health. The aim of the research programme is to develop EHR common data model specifications and to advance knowledge in the field of psychiatry EHR research, including clinical risk prediction modelling. The appointee will … work with a multidisciplinary team of clinicians, data scientists, and data engineers to conduct epidemiological research on large-scale electronic datasets and develop common data model specifications specific to mental health EHRs. The team conducts research using de-identified EHR data acquired through the Clinical Records Anonymisation and Text Extraction (CRATE) and Clinical Record Interactive Search (CRIS) tools More ❯