Fondazione Bruno Kessler (FBK) is a private research institution devoted to excellence in research in numerous disciplines and designated to the role of keeping the Autonomous Province of Trento in the mainstream of European and international research. Each research area is assigned to a specific research center, of which there are twelve totals. Information regarding the research centers, their activities and production is available at http://www.fbk.eu/research-centers .

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.

Job requirements

The ideal candidate should have:

• PhD degree, preferably in the field of Climate Physics, Physics, or a related field;
• Experience in following and handling international projects;
• Advanced understanding of deep learning/machine learning algorithms for weather prediction and climate science;
• Advanced knowledge in handling weather and climate-related data;
• Fluent in Python programming;
• Ability to write robust and well-documented code;
• Good knowledge of written and spoken English;
• Good knowledge of GIT;
• Self-driven attitude and ability to work in a collaborative environment, with a strong commitment to achieve assigned objectives;
• Good communication and relational skills.

Furthermore, the following elements will be positively evaluated:

• Previous experience in fully data-driven weather forecasting;
• Previous experience with downscaling climate data;
• Basic knowledge of HPC systems (e.g., SLURM-based).

Employment

Application

Interested candidates are requested to submit their application by completing the online form ( https://jobs.fbk.eu/ ). Please make sure that your application contains the following attachments (in pdf format):

• Detailed CV including relevant past experiences (as an attached document in PDF format);
• Cover Letter (explaining your motivation for this specific position).

Application deadline: 18/03/2026

Please read our Recruitment Regulations before completing your application.
For further information or technical issues regarding the application, please contact the People Innovation for Research Department at jobs@fbk.eu .