RSS Feed Source: Academic Keys

Research Opportunities

Artificial Intelligence

Work description

The workplan begins with the analysis and preprocessing of historical data, focusing on identifying relevant variables, handling missing and noisy data, transforming textual variables, and storing the data on appropriate platforms. In the second phase, both global models (predicting overall product acceptability) and local models (predicting acceptability for specific consumer segments such as gender or age groups) will be developed using artificial intelligence techniques. Particular attention will be given to managing missing data and ensuring the application of transparent AI, with the goal of supporting decision-making in sensory studies.

The final phase involves applying advanced techniques such as transfer learning and ensemble methods to integrate historical and new data. Language models will be used to adapt data formats for consistency. The main expected outcome is a model that is tested and validated in a laboratory environment and prepared

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RSS Feed Source: Academic Keys

Research Opportunities

Artificial Intelligence

Work description

Develop a prototype AI conversational agent (AICA) based in LLM that answers user-posed questions in natural language about the impacts of the EU’s food system. It will utilise food linked life cycle assessment (LCA), footprint and other data developed within and outwith the project, collated into a central structured database.

Quantitative data will be complemented by information derived from research outputs and other assessments. Training of the AICA will take place via development of common questions inspired by the EU’s policy context and the guidance received via stakeholders.

Academic Qualifications

Quality academic background in Computer Science, Computer Engineering, Artificial intelligence, Data Science or equivalent.

Minimum profile required

In conditions that qualify for enrolment in a PhD program. Quality academic background in Computer Science, Computer Engineering, Artificial intelligence, Data Science or equivalent. Knowledge of Data Science,

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RSS Feed Source: Academic Keys

Job ID: 259016

INESC TEC | Research Initiation Grant (AE2025-0266)
INESC TEC

Research Opportunities

Telecommunications

Work description

Study and analysis of the state of the art in wireless networks, particularly in extreme environments. Collaborate in writing technical reports on the models, mechanisms or algorithms developed. Collaborate in the development of new communications solutions for extreme environments. Write the scholarship activity report.

Academic Qualifications

Frequency in Electrical and Computer Engineering or related field

Minimum profile required

Solid knowledge of the TCP/IP stack and Linux. Proven experience with artificial intelligence models and programming using C++ and/or Python languages. Experience in research and development in the field of computer networks.

Preference factors

Knowledge of wireless networks. Knowledge of simulation.

Maintenance stipend: € 651.12, according to the table of

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RSS Feed Source: Academic Keys

Job ID: 259015

INESC TEC | Research Grant (AE2025-0265)
INESC TEC

Research Opportunities

Computer Science

Work description

Development of deep learning models for remote sensing and detecting of environmental crimes. Development of evaluation metrics to assess and compare the performance of prediction models.

Academic Qualifications

Bachelor degree in Data Analytics, Computer Science and Informatics.

Minimum profile required

Knowledge of mathematics, Data Mining/Machine Learning, Deep Learning, proficiency in programming languages including Python, Keras, TensorFlow, Java and R. Attendance or doctoral candidate in the areas that constitute an admission requirement.

Preference factors

Experience with deep learning and Docker application development.

Maintenance stipend: € 1040.98, according to the table of monthly maintenance stipend for FCT grants , paid via bank transfer. Grant holders may be awarded potential supplements,

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