Master’s thesis in the field of “Monte Carlo Markov Chains methods for the estimation of Gaussian mixtures in remote sensing images using a Bayesian non- parametric approach”

The Bruno Kessler Foundation (FBK) is a research and innovation institution based in Trento. The Foundation operates in a plurality of disciplinary fields and aims to achieve excellence in science and technology through two science clusters, one dedicated to technology and innovation and one to humanities and social sciences, organized in 12 Research Centers, and with more than 450 researchers. For more information visit https://www.fbk.eu/en/about-fbk/.

In this context, the Remote Sensing for Digital Earth (RSDE) Research Unit of the Center for Digital Society deals with the automatic analysis of remote sensing images for Earth Observation and space exploration, consistent with the Foundation's objectives.

More information about the RSDE Research Unit can be found at https://rsde.fbk.eu/.

Planned activities

The RSDE Research Unit is looking for a Master’s student interested in pursuing an internship experience oriented to a Master’s Thesis work in the analysis of remote sensing images using statistic and stochastic methods such as Monte Carlo Markov Chains for Earth Observation tasks.

The ideal candidate is a proactive and dynamic young person with good organizational and interpersonal skills, with a propensity for teamwork, motivated to undertake a training experience in an international context.

The intern, working alongside the Research Unit staff, will mainly contribute to the study and development of Monte Carlo Markov Chain (MCMC) methods for Gaussian mixtures (GMM) in a Bayesian non-parametic (BNP) framework for the modeling of remote sensing data. The activity plan includes: 
 
  • State-of-the-Art analysis on MCMC methods for GMM estimation and their implementation.
  • Search study and use of BNP models in the remote sensing field.
  • Conversion of SoA general estimation methods from R to Python.
  • Design and implementation of novel MCMC models/methods specific for the remote sensing tasks such as change detection.

Requirements
  • Strongly suggested a Bachelor's degree in Mathematics, Physics, or other STEM subject well grounded in Statistics.
  • Knowledge of major subjects related to computer science and image/signal processing.
  • Fluent knowledge of written and spoken Italian and/or English.
  • Relational and teamwork skills.
  • Good adaptability, flexibility and initiative skills.
  • Computer skills in the use of Python, knowledge of R

Internship information

Internship experience duration: 6 months or more, depending on the candidate’s needs.
Opportunity reserved for Bachelor’s graduates with a degree in a subject from those listed in the requirements.
The internship location can be remote, hybrid, or in-person at the Center for Digital Society at the FBK’s premises in Povo, Trento.
We offer support in finding accommodation at affiliated facilities, in the case of off-site candidates.
Possible recognition of participation allowance.

How to Apply

All interested parties are asked to fill out the online form by clicking on "Apply Online" in the "Internship opportunities" section, attaching the following documents in .pdf format:
  • curriculum vitae
  • motivational letter
For any details about the internship activity, please contact Francesca Bovolo at: bovolo@fbk.eu