Research Grants in AI Server Optimization and Resource Management

Two research grants for developing AI server architectures, energy optimization, and dynamic resource allocation at Universidade da Madeira.

Best for:Best for master’s graduates in computer engineering, electronics, or related fields with strong technical skills in AI, distributed computing, and resource management, seeking to advance their research careers through doctoral studies.

Universidade da Madeira · Funchal, Portugal · R1 · First-stage researcher

More professors at Universidade da Madeira

AI server architecturesDistributed computingComputational resource managementEnergy optimization in AI infrastructuresVirtualization and containerizationDynamic resource allocation

Deadline

Oct 13, 2026

Expired

Funding

Stipend

€1.4k/mo

Start date

flexible (within 15 working days of publication)

Full-time

Location

Funchal

Portugal

Overview

This position offers two research grants within the ARIES project at Universidade da Madeira, focusing on AI server optimization, distributed computing, and computational resource management. The successful candidates will conduct literature reviews, analyze technical requirements, and implement virtualization and containerization environments for AI servers. The work involves developing methodologies for efficient resource allocation, evaluating energy optimization strategies, and conducting experimental validations. This opportunity is ideal for motivated candidates with a master’s degree in computer engineering, electronics, or related fields, aiming to pursue doctoral studies or contribute to cutting-edge AI infrastructure research.

AI infrastructure optimizationDistributed computing systemsGPU and CPU resource managementEnergy-efficient computingVirtualization technologiesPerformance benchmarkingDoctoral research grantsPortugal research opportunities

What you'll do

Conduct a comprehensive literature review on AI servers, distributed computing, and computational resource management.
Survey and analyze technical requirements for AI applications across various use scenarios.
Study and compare server architectures, GPU, and storage solutions suitable for AI workloads.
Implement virtualization and containerization environments for shared AI server usage.
Develop optimization strategies and dynamic allocation mechanisms for computational resources.
Create real-time monitoring mechanisms for performance, energy consumption, and resource usage.
Perform experimental validation of proposed solutions through performance, scalability, and reliability tests.
Write scientific articles and disseminate research findings.
Prepare and submit a doctoral thesis based on research outcomes.

Requirements

Degree required: Master's degree in Computer Engineering, Electronics, or a related field.

Degree offered: PhD

Language: English; proficiency sufficient for academic research and communication.

Instruction: English

Required skills

Enrollment in a doctoral program or a non-degree research course in association with a higher education institution and R&D unit.
Proven technical skills in computer engineering or electronics.
Good knowledge of English language (written and spoken).
Experience with literature review and technical analysis.

Nice to have

High motivation and proactivity in research.Strong interpersonal skills and ability to work in a team.Initiative and problem-solving skills.Excellent writing and creativity in research communication.Adaptability and resilience in research environments.Autonomy and persistence in completing research tasks.

Eligibility

Must be enrolled in a doctoral program or a non-degree research course.
Must hold a master’s degree in a relevant field.
No specific nationality or residency restrictions mentioned.

Funding & terms

Type

Stipend

Amount

€1.4k/mo

Duration

6 months (renewable for equal periods until 2029)

Programme

Madeira 2030, Portugal 2030, European Regional Development Fund (ERDF)

EU-FUNDEDEuropean Regional Development Fund (ERDF), Instituto de Desenvolvimento Regional (IDR)

How to apply

Deadline: 2026-10-13 (Atlantic/Madeira)

Submit an application letter along with a letter of motivation, updated CV, copy of qualifications certificate, and proof of enrollment in a doctoral program or non-degree course. Applications can be submitted in person, by mail, or by email to nucleo.bolseiro@mail.uma.pt. Include the scholarship reference in the subject line.

Documents required