Intelligence allows us to learn, imagine, cooperate, create, communicate, and so much more. By better understanding different aspects of intelligence, we can use this knowledge as inspiration to build novel computer systems that learn to find solutions to difficult problems on their own.
Like the Hubble telescope that helped us look deeper into space, these tools are already expanding human knowledge and making positive global impact. Our long term aim is to solve intelligence, developing more general and capable problem-solving systems, known as artificial general intelligence (AGI).
Guided by safety and ethics, this invention could help society find answers to some of the world’s most pressing and fundamental scientific challenges.
To accelerate the field, we took an interdisciplinary approach, bringing together new ideas and advances in machine learning, neuroscience, engineering, mathematics, simulation and computing infrastructure, along with new ways of organising scientific endeavour.
We achieved early success in computer games, which researchers often use to test AI. One of our programs learned to play 49 different Atari games from scratch, just from seeing the pixels and score on the screen. Our AlphaGo program was also the first to beat a professional Go player, a feat described as a decade ahead of its time.
The DeepMind Academic Fellowship Program provides an opportunity for early-career researchers in the fields of Computer Science and Artificial Intelligence to pursue postdoctoral study and build the experiences and research profile that will enable them to progress to full academic or other research leadership roles in future.
Alongside financial support, DeepMind provides opportunities for fellows to be mentored by senior DeepMind researchers. DeepMind will not direct their research and fellows are free to pursue any research direction they wish.
Fellowships are open to early-career researchers who have completed a PhD in Machine Learning, Computer Science, Statistics or another relevant field by the time they start their postdoc. We particularly encourage candidates who identify as Black to apply because this group is currently underrepresented in AI research.
DeepMind has partnered with three UK universities to launch the Fellowship program. For a detailed eligibility criteria, including how to apply, check out our partner university websites or email the contacts provided.
Many on our team hold university professorships and teach or supervise students at Cambridge, Oxford, MIT, Imperial, and elsewhere. Learn more about these courses on our YouTube channel or Learning resources page.
We also partner with many world-leading academic institutions to extend research and teaching capacity. So far, we’ve established academic chairs in machine learning at the University of Alberta, UCL, and the University of Cambridge.
DeepMind established our scholarships programme in 2017 in an effort to help build a stronger and more inclusive AI community, who can bring a wider range of experiences to the fields of AI and computer science. The scholarships provide financial support to students from underrepresented groups seeking to study graduate courses relating to AI and adjacent fields. Scholars are also offered support from a DeepMind mentor, and have opportunities to attend leading AI academic conferences and DeepMind events.
Our dedication to science makes us who we are. That’s why we partner with charities like Chess in Schools and Communities and In2Science, and have become founding partners of the Deep Learning Indaba in Africa, the Eastern European Machine Learning Summer School, and the AI4Good Summer Lab in Canada. We also offer internship programmes for students who want to gain industry experience.
We firmly believe that everyone should feel able to participate in science and we are committed to supporting organisations that create community and advance diversity within the sector. Our team members regularly dedicate their time and expertise to advancing discussions about AI in their communities and we are proud partners of the Anita Borg Foundation, Women in Machine Learning, Black in AI, and more.