RSS Feed Source: Academic Keys

Research Opportunities

Programming, Computer engineering

Work description

The goal of this research is to evaluate how Large Language Models (LLMs) can be leveraged to address forecasting challenges in the energy sector, specifically those that can be framed as sequence-to-sequence problems.

The grant holder will explore different strategies on prompt engineering, compare the potential of different LLM’s and create a methodology that can be replicable to multiple challenges for the energy sector.

Academic Qualifications

Electrical Engineering, Informatics, Computer Science or similar courses.

Minimum profile required

Programming experience in Python. Basic understanding of machine learning concepts. Experience using data science tools (e.g., pandas, scikit-learn, matplotlib). Familiarity with version control systems (Git).

Preference factors

Familiarity with Large Language Models (e.g., Mistral, LLaMA). Understanding of machine learning workflows and forecasting methods. Python oriented to data manipulation and analytics.

Maintenance stipend: € 651.12, according

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RSS Feed Source: Academic Keys

Job ID: 257948

INESC TEC | Doctor Researcher (AE2025-0235)
INESC TEC

Research Opportunities

Computer Science

Work description

Contribution to the preparation of R&D proposal proposals. Development of intelligent models within the scope of electrical energy systems. Supervision of students and scholarship holders to develop work related to the area of work. Development of scientific production oriented to international journals and conferences, and participation in scientific and technological dissemination initiatives.

Academic Qualifications

Ph.D. degree in Computer Science or a related scientific field, and who possess a scientific and professional track record demonstrating a profile suitable for the activities to be carried out, are eligible to apply.

Minimum profile required

Ph.D. holders with experience in the development of data science-based solutions applied to the domain of electric power systems,

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RSS Feed Source: Academic Keys

Research Opportunities

Computer Science; Informatics

Work description

The design and development of automated data pipelines for pre-processing, anonymisation and efficient storage of large volumes of clinical data. The creation of backends and APIs using frameworks to integrate AI models with hospital interfaces. The implementation of security mechanisms and compliance with the LGPD/GDPR and hospital standards. The technical integration of the predictive model with existing hospital systems, guaranteeing interoperability and performance.

Active collaboration with the scientific team in the technical and methodological documentation of the solutions developed and in the writing of scientific publications.

Academic Qualifications

Master’s degree in computer science.

Minimum profile required

Knowledge of Software Engineering. Knowledge of Data Science.

Preference factors

Solid academic background in Computer Engineering, Computer Science. Relevant experience in backend software development and API integration. Knowledge and experience in managing and processing large volumes

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