Computer Science or Electrical or Mechanical Engineer or similar
This work programme considers the participation on the following activities: - Analysis of use cases and definition of the specific goals and requisites(e.g., what data should be used) - Collect data and perform pre-processing (e.g., remove noise, damaged data,...) - Describe the data from the power transformers sensors(e.g., through statistical descriptors) - Study the underlying physical models(e.g. electrical model, mechanical model) - Create empirical models using Neural Networks or methods that are more suitable. - Combine physical models with empirical models and yield hybrid models. - Create/adapt the hybrid models for incremental operations and data streams. - Adapt these behavior models to possible data-driven services. This project involves the collaboration of EFACEC, INEGI and MIT Portugal institutions. It is also predicted the collaboration in lectures activities.
- Licentiate or Master's degree in Computer Science or Electrical or Mechanical Engineering or similar. - The awarding of the fellowship is dependent on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions.
Minimum profile required
- Licentiate or masters final graduation mark higher or equal to 14.- Fluency in English (spoken and written)- Knowledge in Data Generators (Data Synthesis).
- Enrollment in a doctoral program in Electrical, Mechanical Engineering, Computer Science or similar; - Experience in participating in research projects; - Experience in Machine Learning, Data Mining and Power Transformers;
Since 14 Oct 2020 to 28 Oct 2020
Cluster / Centre
Computer Science / Artificial Intelligence and Decision Support