Formulating CONICET Budgets for Computer Science & AI

1. Financial Alignment & Eligibility Standards

Securing research funding from Consejo Nacional de Investigaciones Científicas y Técnicas requires meticulous adherence to both financial eligibility standards and administrative regulations. For projects in the domain of Computer Science & AI, budgets must be constructed using realistic cost projections that are directly tied to the scientific methodology. Under-budgeting may jeopardise project execution, while over-budgeting or including ineligible costs often leads to immediate rejection during administrative screening.

Computational research in Computer Science & AI is heavily weighted toward high-performance computing (HPC) nodes, scalable cloud storage, specialized developer software, and travel for rapid presentation dissemination at international proceedings, which must be clearly justified to CONICET reviewers.

Proposal teams must submit all budget items in the host institution's local currency, mapping them to the specific electronic submission environment (SIGEVA). Every cost item must be justifiable as necessary, reasonable, and allocable to the project.

2. Direct vs. Indirect Cost Categorisation

A primary point of auditing compliance is the strict division between Direct Costs (expenses directly attributable to the execution of the research project) and Indirect Costs (institutional overheads, facility maintenance, and central administrative support).

Institutional overhead recovery is subject to the **CONICET** indirect cap of **Project-specific overhead restrictions**. Host finance teams must audit the budget sheet to ensure this rate is applied accurately to the eligible direct costs of the **Computer Science & AI** project.

For CONICET proposals, the indirect cost rate is structured as: Project-specific overhead restrictions. This rate must be applied correctly to the modified total direct cost base according to your institution's negotiated rate agreement or the flat rate set by the funder.

3. Step-by-Step Budget Justification Protocol

The budget justification (or budget narrative) is a critical component of the application reviewed by both financial auditors and peer reviewers. To draft a compliant narrative:

• Provide granular detail: Do not use lump sums. Break down personnel costs by calendar months or percentage of effort.
• Demonstrate direct linkage: For every cost, explain how it supports a specific task or objective in the research plan for Computer Science & AI.
• Cite institutional policies: Reference verified institutional rates for fringe benefits, travel mileage, and indirect cost bases to validate your numbers.
• Verify supplier quotes: For major equipment purchases or specialized laboratory assays, upload or reference formal vendor quotes.

Pre-Award Framework, Cost Sharing & Post-Award Governance

Securing competitive funding from the Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) for Computer Science & AI research is grounded in professional grant development and institutional pre-award grant management structures. In evaluating categorical grants vs block grants under CONICET policies, investigators will find that these awards operate strictly as categorical grants rather than unstructured block grants. When building the grant proposal timeline, the PI and co-principal investigator must ensure there is sufficient margin for institutional review and formal clearance of any cost sharing on grants. Post-award compliance enforces systematic post-award grant management, which includes drafting a formal subaward agreement research with participating research groups. Under active guidelines, project teams must submit formal effort certification research audits, enabling the PI to track personnel hours during collaborative team science research in Computer Science & AI.

4. Frequently Asked Questions