Positions: 5
Research Grant (BI)
BI|2026/872-Project ORQESTRA
Type of position: Research Grant (BI)
Duration: 6 months
Deadline to apply: 2026-03-27
DescriptionONE (1) research grants for students with MSc degree with reference number BI|2026/872, project ORQESTRA - Refª 101224573, funded by European Commission - Program HORIZON EUROPE, is now available under the following conditions:
OBJECTIVES | FUNCTIONS
Develop high efficient and secure systems based on the neuromorphic computing paradigm. The work to be developed consider security supported on spike-based computing, where computation is triggered by input spikes. The efficiency inherent to this type of processing will be explored also on this new important perspective.
Contact email: bolsas@inesc-id.ptBI|2026/873-Project U2DEMO - Refª 101160684
Type of position: Research Grant (BI)
Duration: 6 months
Deadline to apply: 2026-03-26
DescriptionONE (1) research grants for students with BSc degree with reference number BI|2026/873, project U2DEMO - Refª 101160684, funded by European Commission - Program HORIZON EUROPE, is now available under the following conditions:
OBJECTIVES | FUNCTIONS
Develop optimal scheduling strategies for energy communities with flexible assets. Propose and develop decision support methods for energy communities to participate in multiple energy markets. Evaluate the impact of informed decision-making approaches vs non-informed decision-making approaches. Test the developed algorithms in Lab/real environment.
Contact email: bolsas@inesc-id.ptBI|2026/869-Projet DIME-refª 2024.13433.CMU
Type of position: Research Grant (BI)
Duration: 5 months
Deadline to apply: 2026-03-24
DescriptionONE (1) research grant for students with BSc degree with reference number BI|2026/869 under the scope of the Projet DIME-FS A Decentralized File System – refª 2024.13433.CMU, funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:
OBJECTIVES | FUNCTIONS
This project aims to design and implement DRIFT (Decentralized Reputation Infrastructure for Trust), a novel token-based reputation system designed for decentralized cloud computing platforms governed by Decentralized Autonomous Organizations (DAOs). It tackles the fundamental challenge of establishing trust in peer-to-peer computing resource markets without relying on centralized authorities. DRIFT leverages a unique reputation token that serves both as a governance tool and a marker of reliability, creating strong economic incentives for providers to deliver consistent, high-quality services. The system integrates attestation protocols and a stake-weighted reputation model that dynamically reflects verified contributions of computing resources.
In contrast to traditional centralized cloud reputation frameworks—often opaque and controlled by corporate entities—DRIFT offers a transparent, community-driven alternative. Unlike decentralized platforms such as Filecoin and Golem, which employ rudimentary reputation features, DRIFT’s dual-purpose token introduces a significant innovation by merging governance power with economic rewards. Its stake-weighted scoring mechanism addresses the cold-start problem, enabling new participants to signal credibility through initial token commitments. Moreover, DRIFT’s attestation protocols provide cryptographic guarantees of service quality, surpassing the basic completion metrics used by other systems. This multifaceted approach blends economic incentives with verifiable trust signals, offering a more nuanced and robust reputation framework for decentralized cloud infrastructures.
Contact email: bolsas@inesc-id.ptBI|2026/870-Project ACCELERAT.AI
Type of position: Research Grant (BI)
Duration: 3 months
Deadline to apply: 2026-03-24
DescriptionONE (1) research grant for students with BSc degree with reference number BI|2026/870 under the scope of the Project ACCELERAT.AI – Refª C644865762-00000008 funded by by Recovery and Resilience Plan (RRP) https://recuperarportugal.gov.pt/ and Next Generation EU European Funds, is available under the following conditions:
OBJECTIVES | FUNCTIONS
The remarkable text generation capabilities shown by LLMs have sparked the interest of researchers working in automatic speech recognition to explore approaches to incorporate the speech modality, so that the model can be fine-tuned to perform automatic speech recognition. There are several methods to do this “connection”, including the use of discretised new units and the adaptation of the speech encoder embedding space to that of the language model.
This project proposal will focus in the former. Similarly to previous work [1], we plan to incorporate speech modality via discretized units to a European Portuguese LLM. Some aspects that will require particular attention is the evaluation and selection of the speech encoder for Portuguese, the configuration of the discretization process and the fine-tuning with (likely) less training resources than previous experiments with high-resourced languages, such as English.
Contact email: bolsas@inesc-id.ptBI|2026/865-Projet DIME-FS
Type of position: Research Grant (BI)
Duration: 5 months
Deadline to apply: 2026-03-24
DescriptionONE (1) research grant for students with BSc degree with reference number BI|2026/865 under the scope of the Projet DIME-FS A Decentralized File System – refª 2024.13433.CMU, funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:
OBJECTIVES | FUNCTIONS
The goal of this project is to design and implement an overlay network architecture for DIME-FS, a decentralized file system designed to for high performance. The project will focus on adaptive topology management algorithms that dynamically organize nodes based on geographic proximity, network latency, storage capacity, and trust metrics derived from historical behavior. The data distribution heuristics implement a hybrid replication strategy that balances availability requirements with performance considerations, utilizing a risk-scoring mechanism to identify potentially malicious peers while minimizing unnecessary redundancy. The system uses a reputation-based access control mechanism where data placement decisions incorporate peer trustworthiness scores derived from participation history, network contributions, and validation consensus.
Contact email: bolsas@inesc-id.pt