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Software performance, queueing networks, neural networks, optimization
The successful candidate possesses demonstrated experience in quantitative modeling techniques for software performance engineering using queuing networks or other analytical methods.
Previous experience with the use of machine learning or numerical optimization for the identification or calibration of software performance models is desirable.
Excellent analytical and coding skills are essential.
The successful candidate will work on a research project concerned with building software performance models from data using both white-box models such as layered queuing networks and grey-/black-box models based on deep neural networks. The candidate will be involved in all stages of the research including the development of the methodology and validation on real case studies, particularly from the area of distributed systems developed according to the microservice architecture.
- A Master's degree in Computer Science or related subjects;
- Excellent analytical and coding skills
- An excellent command of the English.
Job Contract Type:
Borsa a progetto - Project fellowship
Apply ONLINE only.
Before filling in the application form, please read thoroughly the full call and collect all the files you may need:
- Personal info and contact info (compulsory);
- University degree (compulsory);
- PhD (compulsory only if stated in the full call).
- The scanned copy of a valid identity document (Passport or Identity Card - compulsory);
- Your CV in English (compulsory).