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Description:

Lightweight fibre-reinforced composites are vital in enabling more efficient wind turbines and making cars lighter. Composite structures face large safety factors, which can make them heavier and more expensive. These large factors are required due to the early damage initiation and the challenges in predicting their damage development. This project will address both aspects with a focus on off-axis cracks. These cracks are usually the first significant damage that initiates upon loading the composite in tension or bending, and are hence a key reason for the large safety factors. Despite their importance, most models for off-axis cracks are limited to 90° plies and 2D. Such models have led to a basic understanding of the initiation phase on the surface, but a very limited understanding of the propagation phase in the bulk of the material.

The key challenge of this PhD project is

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RSS Feed Source: Academic Keys

Job ID: 257553

INESC TEC | Research Grant (AE2025-0211)
INESC TEC

Research Opportunities

Management and annotation of endoscopy images

Work description

Within the scope of the EndoRadiomics project, it is planned to collect, annotate and manage a heterogeneous and large set of data from endoscopic examinations.

The work of the scholarship holder will take place at FCUP’s facilities, with regular visits and meetings to the IPO’s facilities and are developed within the scope of this project, with the following main tasks associated:

Management and annotation of endoscopy images using specialized software. Support to the project team in the tasks of insertion, maintenance and use of data.

Academic Qualifications

Degree in Biology.

Minimum profile required

BSc in Biology. Frequency of a MSc in the scientific area of Biology.

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RSS Feed Source: Academic Keys

Research Opportunities

Computer Science; Informatics

Work description

The acquisition and processing of clinical data, with a focus on cleaning, normalising and structuring it. The application of natural language processing (NLP) techniques, including recurrent neural networks, to analyse free text records and extract patterns. Building predictive models using Python libraries. Evaluating the performance of current screening using statistical metrics such as sensitivity, specificity, precision and acuity.

The production of clear and informative visualisations to support the interpretation of results. Participating in the writing of scientific articles on the methods and results obtained.

Academic Qualifications

Computer science graduate.

Minimum profile required

Knowledge of Software Engineering. Knowledge of Data Science.

Preference factors

Experience in Python programming. Experience in programming and natural language processing (NLP), neural networks or other machine learning techniques. Experience in data visualization. Fluency in written and spoken technical English.

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RSS Feed Source: Academic Keys

Job ID: 257559

INESC TEC | Research Grant (AE2025-0227)
INESC TEC

Research Opportunities

Computer Science

Work description

Collaborate with the VeriFixer team on software development for software fault localization and repair. Collaborate with the VeriFixer team on the writing of scientific papers. Produce a technical report documenting all the tasks performed.

Academic Qualifications

BSc degree in Computer Science and Engineering or similar area.

Minimum profile required

Overall final grade of BSc greater or equal to 16. Proficiency in English. Proven experience in Dafny. Proven experience in software development for the Dafny toolchain.

Preference factors

Preference is given to candidates with proven experience with program mutation techniques.

Application Period

Since 29 May 2025 to 12 Jun 2025

Centre

High-Assurance Software

Scientific Advisor

Alexandra Sofia Mendes

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