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Job ID: 256550

INESC TEC | Research Grant (AE2025-0185)
INESC TEC

Research Opportunities

Mobile Robotics

Work description

Integration with ROS and RealSense camera; Annotation of datasets for training neural networks; Training of neural networks; Integration of the trained model into a pipeline for subsequent estimation of the position of the metal box. Laboratory Tests of the Developed Solution;

Academic Qualifications

Candidate must be enrolled in an undergraduate and/or master’s degree in electrical engineering, computer science or similar;

Minimum profile required

Candidate must be enrolled in an undergraduate and/or master’s degree in electrical engineering, computer science or similar; Experience in C/C++ and/or Python programming.

Preference factors

Participation in extracurricular activities related to robotics or automation is valued; Knowledge of Artificial Intelligence (AI) frameworks; Knowledge of ROS;

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RSS Feed Source: Academic Keys

Research Opportunities

Bioengineering, Computer Engineering and Computing, Electrical and Computing, Artificial Intelligence and Data Science and related areas

Work description

The fellow to be hired will contribute to the development of artificial intelligence-based solutions for automated analysis of polysomnography (vPSG) videos in the context of the diagnosis of sleep disorders, in particular REM sleep behavior disorder (RBD).

The activities to be performed aim to:

Annotation and preparation of data for training and validation of machine learning models, ensuring the quality and coherence of the data sets used. Development and implementation of computer vision algorithms for detecting and analyzing specific RBD behaviors in vPSG videos. Integration and testing of solutions in a simulated clinical environment, ensuring the applicability of the models developed in medical practice. Participation in the analysis of results and in the benchmarking of the system against the manual evaluation of experts,

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RSS Feed Source: Academic Keys

Job ID: 256548

INESC TEC | Research Initiation Grant (AE2025-0182)
INESC TEC

Research Opportunities

Computer Science

Work description

Study methodologies for automatic detection of anomalies or regions of interest; Collaborate in the preparation of suitable datasets; Implement modules for processing the visual information; Writing the grant activity report.

Academic Qualifications

Degree in Electrical and Computer Engineering, Informatics, Computer Science or similar

Minimum profile required

Programming experience (C/C++/Python); experience in computer vision; Experience in deploying machine learning models;

Preference factors

Enrolled in a master course; Experience in the usage of computer vision and machine learning models for object detection in industrial environments.

Maintenance stipend: € 651.12, according to the table of monthly maintenance stipend for FCT grants , paid via bank transfer. Grant holders may be

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