The Rainwater Charitable Foundation has opened a new call through its Tau Consortium, the Learning Research Network (LRN). It will fund research into primary tauopathies that uses artificial intelligence in a way that genuinely changes how the science gets done, with up to $1 million available per project. You do not need to be part of the Tau Consortium already, and applicants from anywhere in the world are welcome.
Letters of intent close at 5pm US Eastern time (9pm UK time) on 30 October 2026, and no extensions or late submissions will be accepted. Invitations to submit a full application go out by 11 December 2026, full applications are due on 12 February 2027, awards will be announced in May 2027 and projects are expected to start between July and October 2027.
What the funding is for
Primary tauopathies are the conditions driven mainly by abnormal tau, including progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), Pick’s disease and some forms of frontotemporal dementia. The Foundation wants projects that tackle an important biological or translational question in these conditions, whether that is disease mechanisms, diagnosis, patient stratification, biomarkers or treatment, including new therapeutic hypotheses and targets.
The AI element is not optional decoration. It has to be integral to the approach and give a clear scientific or collaborative advantage over traditional methods, and reviewers will judge both how well AI is integrated and whether it is technically feasible. That said, you do not have to build a new AI agent or software platform. Using AI to analyse data, generate and test hypotheses or support collaboration is fine, provided its role is meaningful and well justified. For a sense of what AI can already do at the bench, read our blog on the transformative potential of AI on basic science.
Areas of interest
- AI-ready data. Creating FAIR (findable, accessible, interoperable and reusable), well curated datasets built for reuse, with proper metadata, documentation and standards, including harmonised or benchmark datasets.
- AI-enabled collaboration and workflows. Shared research environments that connect data, analyses, workflows and knowledge, which could mean reusable AI agents, analysis pipelines, APIs or workflow tools.
- Strengthening the field. Lasting, interoperable infrastructure, tools, standards or practices that others can adopt, such as knowledge graphs, foundation models, data sharing frameworks and autonomous or semi-autonomous research workflows.
The Foundation describes the LRN not as a single database or platform but as an ecosystem of connected resources that researchers, and increasingly AI tools, can build on. Your project does not need to build the LRN itself, but outputs that others can reuse beyond your own project will strengthen your application. Data, systems and programs produced under the award should be available for scientific reuse within six months of the project ending, although not everything has to be open source. If you need convincing that sharing pays off for you as well as the field, read our blog on selfish reasons for open science.
Funding and team size
Each participating laboratory or technical team can receive up to $250,000, and a project can involve up to four teams, giving a maximum budget of $1 million. Collaboration is strongly encouraged but not required, and teams can come from the same institution or different ones. The award is made as a single grant to the coordinating PI’s institution, which then handles subawards to its partners.
Two points to take to your research office early. First, no indirect costs are paid, on either the main award or any subawards, which your institution will need to agree to. Second, the guidance on the budget template states that the program must not run for more than 12 months, a tight window for work on this scale, so plan your timeline and costs with that in mind.
Who can apply
The lead applicant must direct an independent program, laboratory, engineering team, data resource or equivalent research unit, and be able to receive and administer funding through their organisation. That includes faculty at Assistant Professor level or above (roughly lecturer or above in the UK), as well as scientific, engineering, nonprofit or industry leaders who can show independence and relevant expertise. Academic, medical, research, nonprofit and commercial organisations anywhere in the world are eligible, although for-profit awardees face extra due diligence and reporting.
The Foundation is openly keen to hear from engineers, data scientists and computational researchers as well as biologists, so this could suit someone with strong AI or data skills who has not worked on tau before, teamed up with a lab that has. If you are an early career researcher not yet leading your own group, this is one to take to your PI or to a collaborator who could coordinate a bid.
The letter of intent
The LOI asks for:
- a project title and details for the coordinating PI and up to three further PIs or team leads
- a non-confidential lay abstract of up to 350 words
- a research plan of up to two pages, including figures
- an LRN Contribution and Integration Plan of up to half a page, uploaded separately and not counted within the two pages
- a budget using the Foundation’s template
- current biosketches or short CVs for every PI or team lead
- an optional one-page reference list
The integration plan should set out the datasets, software, agents, APIs or workflows you expect to produce and how they could feed into the LRN, covering interoperability, documentation, data access, storage estimates and how the wider community might adopt them. Funded teams will also be expected to work with the LRN technical team and take part in relevant Tau Consortium and LRN working groups.
LOIs are assessed on their potential to advance understanding, diagnosis, stratification or treatment of primary tauopathies; AI integration and technical feasibility; innovation; data management and sharing; degree of collaboration; potential to strengthen neurodegenerative research; potential to create lasting capabilities for the LRN and beyond; and the quality of the integration plan. The Foundation notes that secure AI-assisted tools may help organise and analyse applications during review, but funding decisions are made by people. Before you start writing, listen to our podcast on grant writing tips from awardees and reviewers.
How to apply
Preview the LOI questions first, then submit through the Foundation’s online application portal. Questions about the call can go to medgrants@rainwatercf.org.
Read the full details and apply
Why it matters
There are still no disease-modifying treatments for the primary tauopathies, and research into them is spread across small groups working on rare conditions. That is where shared, reusable data and tools make the biggest difference, because no single lab has enough patients, samples or data on its own. For a flavour of the tau science the Foundation backs, listen to our podcast with the Rainwater Prize winners on advancing tau research, and for where AI in dementia research is heading, try our episode on agentic AI and the future of dementia research.
Visit funding web page
(https://rainwatercharitablefoundation.org/medical-research-program/the-tau-consortium/learning-research-network-lrn/)
