진학프로석·박사 채용 접수 플랫폼

Workplace

The Digital Industry Center is one of the Centers of FBK. It focuses its research on digital technologies for the various domains in industry (e.g., manufacturing, aerospace, railway, automotive, energy, agriculture, manufacturing) by creating applications for critical systems, adaptive and autonomous systems, advanced perception, diagnostics, quality control, and prediction systems. Further research areas include precision farming, robotics, metrology, cultural heritage, and geomatics.

The Data Science for Industry and Physics (DSIP) Research Unit focuses on applying Data Science methodologies and approaches to develop predictive machine-learning models from heterogeneous data. DSIP is actively collaborating with industrial partners and research organizations. DSIP is involved in developing Deep Learning solutions for time-series analysis and forecasting in the context of condition monitoring and predictive maintenance for industrial process forecasting and control. In the earth and climate sector, DSIP is involved in projects ranging from machine learning applied to spatiotemporal data for weather nowcasting and forecasting, Earth System Modeling, statistical downscaling, data quality, and anomaly detection of observations. As for applications in physics, DSIP is developing Deep Learning solutions for data analysis in high-energy physics experiments and in space physics.

FBK actively seeks diversity and inclusion in the workplace and is also committed to promoting gender equality. To promote the inclusion of disabled staff as per law 68/99, the Foundation is available and interested in evaluating the applications received for technical-scientific domains that do not correspond exactly to this call.

Job Description

FBK is looking for candidates to fill one position in Deep Learning methods applied to projects within the DSIP unit of the DIcenter.

The successful candidate will work closely with researchers to leverage machine learning and deep learning solutions for weather and climate applications, contributing to the following tasks:

• • Develop machine learning and deep learning models for weather and climate (e.g., nowcasting, climate downscaling).
• • Design and follow projects related to AI models for weather and climate
• • Supervise junior developers and researchers
• • Stay current with the latest developments in Deep Learning frameworks for weather forecasting and climate science.