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We are seeking a highly motivated and experienced researcher to join our team at LNEC, I.P. as an Expert in Data Quality and Reliability. The successful candidate will be responsible for conducting research to develop innovative methodologies and techniques to ensure the quality and trustworthiness of data sources.
The primary aim is to enhance the reliability, validity, and overall quality of data used in computational models and retrieved from monitoring systems. This includes exploring cutting-edge techniques in data preprocessing, feature engineering, and anomaly detection to improve data quality and reliability.
The Expert will be an integral part of a collaborative team and will be responsible for conducting research to develop AI models that can adapt to dynamic and evolving data environments, incorporating mechanisms for robustness, fairness, and transparency.
Key Responsibilities:
- Developing and implementing data validation and verification procedures to identify and mitigate potential errors or biases in data collection, storage, and processing pipelines.
- Employing AI techniques to detect structural anomalies, predict maintenance needs, and optimize inspection schedules to ensure the safety and longevity of critical infrastructures.
- Cultivating relationships with relevant stakeholders in industry and public institutions to identify emerging trends and challenges in data quality and AI applications.
- Actively participating in national and international research initiatives and consortia to expand the reach and impact of the candidate's research.
Requirements:
- PhD degree in Computer Science, Data Science, or a related field.
- Strong background in machine learning, programming languages such as Python or MATLAB, and experience working with large-scale datasets.
- Excellent analytical and problem-solving skills, with the ability to communicate complex concepts effectively to both technical and non-technical audiences.
