Accelerate-C2D3 Funding call for novel applications of AI for research and innovation
The Accelerate Programme in collaboration with C2D3 is offering small grants for Cambridge University researchers pursuing innovative applications of AI, in research or real-world contexts. Funding can support a variety of activities, including research, staff time, events, workshops, teaching, software development, or software development, with a focus on interdisciplinary collaboration.Read More
Join our team! Applications open for a Programme Coordinator to join the Accelerate Programme
We are seeking an experienced Programme Coordinator to ensure smooth running of the Accelerate Programme’s activities and help build a community of scientists working at the interface of machine learning and the sciences. The role holder will help ensure that the Programme operates efficiently by developing administrative processes, organising events, ensuring effective communications across stakeholder communities and monitoring expenditure. The role is offered on a part-time basis at 0.5 fte. Deadline 25 June.Read More
Join our team! Applications open for a Senior Machine Learning Engineer to join the Accelerate Programme
We are seeking a Senior Machine Learning Engineer to lead the Accelerate Programme’s software engineering activities. This will include providing software engineering support (e.g. through the programme’s Machine Learning Engineering Clinic), advising on the development of research projects and delivering training and mentoring to researchers across the University. Deadline 7 July.Read More
Join our team! Applications open for a Research Assistant/Research Associate in AI Interfaces to join the Accelerate Programme.
We are looking for a Research Assistant/Research Associate to join our team, working on a project that explores the interfaces that can facilitate effective interactions between humans and AI. This project could explore different aspects of human-machine collaboration for science, including mechanisms for knowledge exchange between humans and AI, human-computer interactions, and the integration of different model types to deliver new AI for science tools. Deadline 7 July.Read More
Join our team! Applications open for a Senior Research Associate to join the Accelerate Programme.
We are looking for a Senior Research Associate to join the team, with a post that will support them in developing their research careers. The successful candidate will be responsible for pursuing high-quality research at the interface of machine learning and the sciences, delivering teaching and learning activities and contributing to engagement activities. The focus of their research will be the development of AI systems and tools that work for researchers in the scientific context, enhancing the interfaces between science and AI. This might include aspects of human-machine collaboration for science, mechanisms for knowledge exchange between humans and AI, human-computer interactions, and the integration of different model types to deliver new AI for science tools. Deadline 7 July.Read More
Machine Learning Engineering Clinic
The Machine Learning Engineering Clinic seeks to support Cambridge University researchers using AI in their research, by helping resolve engineering issues they might encounter when implementing machine learning methods.Read More
Next Data Pipelines School - 25-26 September 2023
How can researchers design and implement data pipelines for scientific research? Our Data Pipelines for Science School will help scientists to learn how to correctly, efficiently and robustly prepare your datasets for machine learning in your scientific projects.
We are pleased to announce that Accelerate Science will run the Data Pipelines school again in September 2023.Read More
Python and Pandas E-Learning Module
An open e-learning module from Accelerate and Cambridge Spark offering training in Python programming for research challenges.
This self-paced learning module (1-3 days) is designed for researchers across disciplines who want to begin building their data skills to help answer their research questions. This is a great entry point to start working with data to provide the foundations needed to work on more advanced data science and AI techniques.Read More
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