A Researcher in the Field of Deep Learning for Weather and Climate Applications

27 Feb 2026
Job Information

Organisation/Company

Fondazione Bruno Kessler

Department

Unità People Innovation

Research Field

Technology » Computer technology

Researcher Profile

Recognised Researcher (R2)

Positions

Postdoc Positions

Application Deadline

18 Mar 2026 - 23:59 (Europe/Rome)

Country

Italy

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

38

Offer Starting Date

1 Apr 2026

Is the job funded through the EU Research Framework Programme?

Not funded by a EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

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.

Where to apply

Website

https://jobs.fbk.eu/Annunci/Offerte_di_lavoro_A_Researcher_in_the_Field_of_Deep…

Requirements

Research Field

Physics

Education Level

PhD or equivalent

Skills/Qualifications

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).

Level

Good

Additional Information
Benefits

Employment

Type of contract: fixed-term contract

Working hours: Full time (38 h per week)
Start date: Preferably April 2026

Duration: 24 months, with the possibility of extending the contract depending on funding

Workplace: Povo, Trento

Gross annual salary: about € 44.500, plus objective achievements bonus

Benefits: flexi-time, company subsidized cafeteria or meal vouchers, internal car park, welcome office support for visa formalities and for research in accommodation, accommodation etc., supplementary pension and health fund, social security (SANIFONDS), family-work balance, free training courses, support on bank account opening, discount on public transport, sport, language course fees, counseling and psychological support service. More info at https://www.fbk.eu/en/work-with-us/

Eligibility criteria

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).

Work Location(s)

Number of offers available

1

Company/Institute

Fondazione Bruno Kessler

Country

Italy

State/Province

Trentino Alto-Adige

City

Trento

Geofield

Contact

City

Trento

Website

http://www.fbk.eu/

Street

Fondazione Bruno Kessler - Via Sommarive 18 I-38123 Trento/Povo

Postal Code

38123

E-Mail

jobs@fbk.eu

STATUS: EXPIRED

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