THREE POSITIONS AS JUNIOR DEVELOPER IN THE FIELD OF DATA SCIENCE FOR INDUSTRY

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.
., 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 for developing predictive models based on machine learning 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 forecast 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 the data analysis of High Energy Physics experiments in the ATLAS collaboration @CERN and for Space Physics within the CSES-LIMADOU mission.
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 , 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 three positions in Deep Learning methods applied to projects of the DSIP unit of the DIcenter.
The successful candidates will work closely with researchers to operationalize research prototypes, machine learning and deep learning solutions for time series forecasting and anomaly detection.
Responsibilities.
Operationalize machine learning and deep learning models.
Optimize performance and scaling of the solutions.
Stay current with the latest developments in Deep Learning frameworks for time series analysis and forecasting.
Job Requirements The ideal candidate should have.
Master's degree in Computer Science, Data Science, or a related field (the degrees must be obtained by the start date of the FBK contract); Fluent in Python programming; Advanced understanding of deep learning/machine learning algorithms and pipelines for regression/classification tasks and unsupervised tasks (e.
., VAE); Ability to write robust and well-documented code; Good knowledge of written and spoken English; Ability to work in a collaborative environment, with a strong commitment to achieve assigned objectives; Good knowledge of GIT and docker.
Furthermore, the following elements will be positively evaluated.
Data cleaning and preprocessing pipeline; CI/CD pipeline; Basic knowledge of HPC systems (e.
.
SLURM based); Tools for manual labeling; Basics in LMM.
Employment Type of contract.
Fixed term contract Working hours.
full time (38h per week) Start date.
preferably January Duration.
24 months Gross annual salary.
about € Benefits.
flexi-time, company subsidized cafeteria or meal vouchers, internal car park, welcome office support for visa formalities and for research in accommodation, social security (SANIFONDS), family-work balance, free training courses, support on bank account opening, discount on public transport, sport, language course fees, counselling and psychological support service.
More info at https://www.
bk.
u/en/work-with-us/ Workplace.
Povo, Trento (Italy).
Application Interested candidates are requested to submit their application by completing the online form (https://jobs.
bk.
u/).
Please make sure that your application contains the following attachments (in pdf format).
Detailed CV; Motivation letter Application deadline.
14th October Please read our Recruitment Regulations before completing your application.
For further information, please contact the Human Resources Services at .