Sort by
Refine Your Search
-
Listed
-
Field
-
.; - Develop skills in artificial intelligence and machine learning techniques for analyzing operational data and detecting anomalies, using foundational model approaches (e.g., GridFM project, LF Energy
-
with simulation techniques, energy efficiency models, large-scale energy consumption data, machine learning techniques and interpretation (unsupervised); - Education, experience and research orientation
-
with a focus on traditional machine learning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including the development of data analysis and visualisation pipelines. 5
-
, algorithms with a focus on traditional machine learning (shallow learning) and deep learning methodologies. Knowledge of Data Science, including the development of data analysis and visualisation pipelines. 5
-
3 Sep 2025 Job Information Organisation/Company INESC TEC Research Field Computer science » Computer systems Researcher Profile First Stage Researcher (R1) Country Portugal Application Deadline 8
-
Education Institutions. Preference factors: Experience in research activities Minimum requirements: Knowledge of Computer Vision and Machine Learning 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS
-
benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
-
Requirements Academic qualifications: BSc in Computer Science, Computer Engineering or similar. Minimum profile: Enrolled in a Master’s program in the relevant admission area., Knowledge of Machine Learning
-
., PyCaret, scikit-learn). Research FieldComputer science » Computer systemsYears of Research ExperienceNone Additional Information Benefits Maintenance stipend: 1309.64 euros, according to the table of
-
domain in the design of deep learning algorithms for cardiovascular disease detection. 4. REQUIRED PROFILE: Admission requirements: Master's degree in Biomedical Engineering, Computer Engineering