Design and prototyping of new Machine Learning algorithms for Predictive Maintenance purposes
Thesis in external company
External reference persons Davide Mazzucchi (email@example.com)
Description Zirak is an Italian SME company, established in 2000, with an Italian headquarter and a Portuguese R&D lab, providing high quality Information Technology services and extensive support on automotive related topics, from architectural analysis and requirements management to implementation and validation of customized state-of-the-art solutions.
We have also contributed to several M2M projects (e.g. dynamometric key interfacing system, sanitification system for hospital unit spaces and electric bike-sharing platforms), and we have designer our own IoT plaform for predictive logistics / maintenance in collaboration with major European R&D centers.
In the context of an ongoing project of the Zirak embedded department, we propose a thesis in the IoT sector, which sees as its objectives:
1. the in-depth review of the current machine learning algorithm used by Zirak current predictive logistics platform (REDtag), and the proposal of alternative ones, based on state of the art technologies, with an eye to handling different type of data so as to satisfy the predictive maintenance use cases that will be identified with the company tutor (e.g. in train industry) also based on data availability of the same data sets.
2. The best suited algorithm shall then be identified and prototyped, with training and application examples on new data sets.
3. testing of log profiling platforms (such as Splunk) and alternative solutions for the integration with legacy sensors data.
See also www.zirak.it
Required skills The candidate is required to have the following skills and competences:
- Good knowledge of Python
- Good knowledge of artificial intelligence methods and machine learning techniques
- Experience with the following libraries is preferred: scikit-learn, TensorFlow or similar
- Basic knowledge of Jupyter framework
- Good attitude to teamwork
- Good level of spoken and written English
Notes availability to travel to Mondový part-time (60% time).
Deadline 02/10/2020 PROPONI LA TUA CANDIDATURA