Organisation/Company Instituto Politécnico de Coimbra Department DGRH Research Field Other Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal Application Deadline 9 Dec *********:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 16 Jan **** Is the job funded through the EU Research Framework Programme?
Not funded by a EU programme Reference Number PRBI/******* Is the Job related to staff position within a Research Infrastructure?
No
Offer Description
The Polytechnic University of Coimbra opens a call for one research fellowships (BI), in the framework of the the CRIARTE project – Ref.: COMPETE****-FEDER-****************, co-financed by the Portugal **** program – European Regional Development Fund (ERDF) through the Thematic Program Innovation and Digital Transition – Compete ****, under the following conditions:
The scholarship aims to support the implementation and development of the following activities:
Sensor Integration and Robotic Perception
Expertise in sensor fusion and sensor calibration;
Experience withLiDAR, RGB-D/multimodal cameras, GNSS, IMU, UWB sensors, and IoT devices;
Proficiency in ROS/ROS2 (Robot Operating System) and middleware for data integration;
Knowledgeof temporal and spatial synchronization of sensors and extrinsic/intrinsic calibration.
Computer Vision and 3D Pose Estimation
Strong background in computer vision and machine learning applied to pose estimation and visual servoing;
Experience withOpenCV, PCL (Point Cloud Library), PyTorch/TensorFlow, and 3D frameworks such as COLMAP and Open3D;
Ability to develop algorithms for object detection and tracking, 3D reconstruction, and SLAM.
Advanced Control and Intelligent Robotics
Solid knowledge of classical and modern control theory (PID, adaptive, robust, and fractional control);
Experience withfuzzy logic and AI-based control (reinforcement learning, neuro-fuzzy systems);
Skills inmodelling and simulation of dynamic systems (MATLAB/Simulink, Gazebo);
Familiarity with robotic manipulators and manipulator kinematics/dynamics.
Digital Twin Development and Simulation
Experience in digital modelling of robotic systems and cyber-physical integration;
Knowledgeof digital twin tools such as Unity, Unreal Engine, Siemens NX, and MATLAB Simscape;
Ability to represent complex kinematic and dynamic models, including noise and sensor uncertainties.
Applied Artificial Intelligence and Data Analysis
Proficiency in multivariate analysis techniques (PCA, regression, clustering) and predictive risk models;
Experience withartificial neural networks and fuzzy systems for KPI aggregation;
Knowledgein data engineering, Python, and real-time data analysis.
Generic Scientific Area: Electrical Engineering or Computer Engineering
Specific Scientific Area: Automation and Robotics
Master's degree in Electrical Engineering or related fields;
enrolled in a PhDprogram or a non-degree course.
Experience in:
a) ROS, programming in C++ and Python;
b) Modelling and control.
Work Plan:
The work plan is divided into five phases:
Phase 1 – Development of Software for Advanced Sensor Integration.
Objective: Create a sensor integration infrastructure combining data from multiple sensors and human inputs.
Activities: Survey and characterization of robot sensors (LiDAR, multimodal cameras, GNSS, IMU, etc.) and external sensors (CCTV, UWB, IoT);
development of data acquisition, filtering, and preprocessing pipelines;
implementation ofsensor fusion algorithms for temporal and spatial integration;
integration of human inputs from Augmented Reality (A3) devices and other collaborative sensors;
validation tests in simulated and real environments.
Phase 2 – Design of AI Architecture for 3D Pose Estimation.
Objective: Develop an AI architecture capable of estimating the 3D position and orientation of objects with robustness and adaptability.
Activities: Implementation of visual servoing and 3D pose estimation algorithms;
integration of adaptivecontrol techniques, including fractional PID and fuzzy logic;
development of modules to handle uncertainty and noise in visual data;
performance testing under various construction scenarios and environmental conditions;
dynamic adjustment of control parameters for maximum precision and robustness.
Phase 3 – Development of Control Architecture for Sandwich Panel Manipulation.
Objective: Create an advanced and collaborative control system for precise and safe manipulation of panels.
Activities: Modelling of panels and manipulation devices based on environmental sensors;
implementation ofvisual servoing for dynamic control of panel position and orientation;
application of advancedcontrol methods (PID, fuzzy logic, fractional control) to reduce errors;
integration of perception and control systems to adapt to obstacles and environmental variability;
experimental validationof manipulation accuracy, safety, and efficiency.
Phase 4 – Development of the Robot Digital Twin.
Objective: Create a detailed digital model of the robotic platforms for simulation, analysis, and optimization.
Activities: Nonlinear kinematic and dynamic modelling of mechanical components (rotary and linear joints);
integration of accuratesensor models (LiDAR, multimodal cameras) including associated errors;
simulation of robot behavior under various operational conditions;
optimization tests of the perception-action architecture;
predictive analysis of potential failures and continuous performance improvement.
Phase 5 – Integration of Key Performance Indicators (KPIs).
Objective: Create a risk assessment system based on data from assets, humans, and robots to support decision-making.
Activities: Definition of a multidimensional matrix of KPIs and risk levels;
development of indicator aggregation techniques (weighted average, direct sum, PCA, multivariate regression, fuzzy logic, ANN);
implementation ofdynamic risk score adjustment based on the actual execution state;
simulation and analysisof risk evolution during project execution;
optimization of resource allocation and decision-making support using integrated KPIs.
The scholarship aims to support the implementation and development of the following activities:
Sensor Integration and Robotic Perception
Expertise in sensor fusion and sensor calibration;
Experience withLiDAR, RGB-D/multimodal cameras, GNSS, IMU, UWB sensors, and IoT devices;
Proficiency in ROS/ROS2 (Robot Operating System) and middleware for data integration;
Knowledgeof temporal and spatial synchronization of sensors and extrinsic/intrinsic calibration.
Computer Vision and 3D Pose Estimation
Strong background in computer vision and machine learning applied to pose estimation and visual servoing;
Experience withOpenCV, PCL (Point Cloud Library), PyTorch/TensorFlow, and 3D frameworks such as COLMAP and Open3D;
Ability to develop algorithms for object detection and tracking, 3D reconstruction, and SLAM.
Advanced Control and Intelligent Robotics
Solid knowledge of classical and modern control theory (PID, adaptive, robust, and fractional control);
Experience withfuzzy logic and AI-based control (reinforcement learning, neuro-fuzzy systems);
Skills inmodelling and simulation of dynamic systems (MATLAB/Simulink, Gazebo);
Familiarity with robotic manipulators and manipulator kinematics/dynamics.
Digital Twin Development and Simulation
Experience in digital modelling of robotic systems and cyber-physical integration;
Knowledgeof digital twin tools such as Unity, Unreal Engine, Siemens NX, and MATLAB Simscape;
Ability to represent complex kinematic and dynamic models, including noise and sensor uncertainties.
Applied Artificial Intelligence and Data Analysis
Proficiency in multivariate analysis techniques (PCA, regression, clustering) and predictive risk models;
Experience withartificial neural networks and fuzzy systems for KPI aggregation;
Knowledgein data engineering, Python, and real-time data analysis.
Generic Scientific Area: Electrical Engineering or Computer Engineering
Specific Scientific Area: Automation and Robotics
Requirements:
Master's degree in Electrical Engineering or related fields;
enrolled in a PhDprogram or a non-degree course.
The grant has a duration of 12 months, possibly renewable for identical periods on an exclusive basis, according to the Research Grant Regulations of the Polytechnic Institute of Coimbra – Order No. *********, of *****, with expected start after 16th January ****.
Master's degree in Electrical Engineering or related fields;
enrolled in a PhDprogram or a non-degree course.
Experience in:
a) ROS, programming in C++ and Python;
b) Modelling and control.
Selection process
Selection Criteria
- Curriculum Evaluation (70%) and Interview (30%).
- Curriculum Evaluation: Overall merit of CV (70%);
- Publications inconference proceedings and journals (30%);
- InterviewEvaluation:
- Knowledge and suitability for the role (50%);
- Availability and schedule flexibility (20%);
- Motivation and interest (30%)
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