FDL Africa 2027 Application Form

Welcome to FDL Africa

The Frontier Development Lab (FDL.ai) is a network of researchers, partner space agencies, universities and leaders in AI. Founded by Trillium Technologies, it has been running in the USA since 2015 and in Europe since 2018. 2027 will be the first year that FDL will come to Africa.

FDL’s goal is to lead the way in the application of AI in space and apply these new techniques in a safe, ethical and reproducible way for the good of all humankind. FDL is award winning, with over 50 applied AI firsts, including producing federal flood maps of the Australian floods 2022 and Valencia floods 2024 the first AI trained in space and the first demonstration of an AI scientist.

Over the past few years we’ve been leading in the development of a new class of AI called foundation model. These new models present a profound leap in democratising AI, shifting development from months with senior data scientists to a few days with relative newcomers. FDL Africa has been designed specifically to take advantage of this development.

You can read more about FDL and the results from around the world at fdl.ai.

This form helps us get to know you. Take your time, be honest, and show us what lights you up. We’re not looking for perfection, we’re looking for purpose and a willingness to make the world a little bit better. We’re looking forward to hearing about your research interests and working together to tackle some of the most pressing challenges facing our world today.

The whole process takes around 15 minutes and requires a CV.

Make some coffee and dive in!

Ad Astra per Algorithmos

The FDL Africa Team
Part 1: Introduce yourself

Let’s start with the basics so we know how to reach you.

* Indicates required fields
What is your full name?

First NameLast Name
What is your primary email address?
example@example.com
What is your Google email address (if you have one)?
example@example.com
What is your current institution/affiliation (university, employer, etc.)?
What is your current title?
Please share your LinkedIn profile link.
Please share your personal website link.
Please share your Github/Gitlab profile.

Part 2: Research interests & passions

Tell us what you’re great at, what you care about and where you want to go next. This helps us match you with the right challenge.
What best describes your current focus? Choose the one that feels closest to your work (we know many FDLers are hybrids)
Tell us a bit about yourself, including your background and areas of expertise (300 words).
What lights you up? Where have you made an impact? What are you hoping to grow into?
What’s your superpower? (Max 10 words)
Make it punchy and specific, this helps us match you with the right challenge. E.g., ‘hydrology systems’, ‘energy systems’, ‘Africa ecology’, ‘remote sensing for disaster response’,’generative AI for science comms’, ‘SAR change detection’.
Each FDL team is composed of four team members (supported by one or more faculty members), creating a breadth of interdisciplinary skills. The ideal is to have an experienced data scientist (who is comfortable with all of the tools and machine learning approaches) and a subject matter specialist (who knows the problem well and the kind of data that might be useful). The third and fourth team members can be all-rounders - ideally with strong Python and data science skills, who might have worked on similar problems in the past and can bring fresh ideas and approaches and support the scientific goals.

Three priority themes have been identified for FDL Africa. A specialist scientific committee is working on developing the briefs for the final teams. But, at this application stage, we have purposefully kept the subject themes as broad as possible.

One team will be oriented toward modifying a geospatial foundation model for Africa. The team will be focused primarily on building solutions for data pipelines focused on African use cases and settings. The other teams will focus on application and end user pipelines.
Below is a brief description of the FDL Africa 2027 challenges, these will become more focused in the coming weeks, please tick all the challenges that you have any experience or interest in.

Space data for hydrology systems (including flooding, water availability and quality).
AI has already proven adept at interpreting space data to understand the function and health of water supply networks. Other variables such as turbidity and eutrophication are also visible in spectral data. This research theme explores whether geospatial foundation models are able to fast-track water management challenges, leveraging the ability of AI and space data to audit but also predict the status of hydrology systems.Energy systems and climate (including power availability, off-grid systems, digital connectivity, low CO2 and soot).
The energy mix is changing quickly. Strategies need to balance decarbonisation and methane reduction with economic uplift, improved health and digital connectivity. AI is now used to track solar panels and wind farms as well as emissions and twin electrical grids. Can Geospatial foundation models help to analyse optimal energy strategies? Where best to locate green energy projects; how to mitigate negative impact and how to best optimise infrastructure.Mapping and ecology (informal settlements, roads and infrastructure).
Many maps in Africa remain incomplete. Space data can help. AI can use satellites to identify settlements, roads, crop types, economic activity and the movement of flora and fauna. How all these variables interact to create a successful and modern society has been until now, an impossibly complex analysis task. Foundation models and LLMs promise to revolutionise geospatial understanding and planning, classifying and measuring resources, but also extrapolating and running twins of socio-ecological systems to unlock a new era of advanced decision making.
Please share your CV

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Part 5: Work authorization & location

To help us with planning and logistics, we’d like to understand your current work authorization status. This isn’t a make-or-break factor, but it helps us get ahead on what may be needed to support your participation. We will be prioritising applications from researchers with direct knowledge of African data sets and/or applications of geo data and/or using Foundation models or AI for Africa.
What is your primary country of legal citizenship?
Do you hold citizenship or permanent residency in any additional countries?
Will you need a visa to visit South Africa?

Other
Where will you reside during January-May 2027? (City and country)
Is there anything we haven’t asked that you think we should know? We’d love to hear it.
We’re honored you’ve chosen to share your story with us. We treat your data with care, use it only to support the FDL selection process, and will never share it externally.
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Part 4: Availability & expectations