A grant, with Google Deep Mind
Nurturing Grant to Makerere
Call ID: RU/RMRN/2026
Loss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the difference between predicted outputs and ground truth labels, guiding the optimization process …
- Closes
- 29 Oct 202615:58 UCT
- Budget ceiling
- 500,000.00
- Maximum awards
- Open
Why this call exists
Loss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the difference between predicted outputs and ground truth labels, guiding the optimization process to minimize errors.
Scope
Loss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the difference between predicted outputs and ground truth labels, guiding the optimization process to minimize errors.
How to apply
Loss functions are at the heart of deep learning, shaping how models learn and perform across diverse tasks. They are used to quantify the difference between predicted outputs and ground truth labels, guiding the optimization process to minimize errors.
Programme details
- Grant period
- 01 Dec 2026 to 06 Oct 2028
- Eligible costs
- Research costs, Transport
- Key dates
-
- 14 Oct 2026Training
- 26 Jul 2027Publications
- Questions
- cgs@ruforum.org
Who can apply
- Nationality / country — Kenya, Portugal, Uganda (citizenship or institution country or refugee residence)
- Scholarship: target university allow-list — one of 2 listed universities
Documents you'll need
- CV with three referees — Lead applicant's CV, listing three referees with their contacts.
- Research proposal — gdhdhdh
- Proof of affiliation — Letter from your institution confirming your appointment or registration.