Current positions
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1-year PostDoc position (Expired)
we are looking for candidates for PhD and PostDoc positions at the SmartData Center of Politecnico di Torino (Italy) in the context of the H2020 PIMCity European project.
PIMCity European Project:
The Web economy has been revolutionized by unprecedented possibility of collecting massive amounts of user personal data, which lead the web to become the largest data market and created the biggest companies in our history. Unfortunately, this change has deep consequences for users, who, deprived of any negotiation power, are compelled to blindly provide their data for free access to services, and creating a privacy nightmare.
Personal Information Management Systems (PIMS) aim to give users back control over their data, while creating transparency in the market. However, so far, they have failed to reach business maturity and sizable user bases. The PIMCity European Project will offer tools to change this scenario. The project aims at designing and deploying novel mechanisms to increase users’ privacy, studying privacy preserving analytics and automatic methodologies to compute privacy-related metrics.
Job Location:
SmartData center at Politecnico di Torino, Italy – smartdata.polito.it
Research Description:
The candidate will conduct high-quality research activities within the SmartData@Polito center, led by Prof. Marco Mellia, to research on topics including but not limited to:
- Web Privacy Data analytics, to quantify and automatically detect privacy violations and threats on the internet. The candidate will exploit active and passive measurements to fed automatic algorithms to detect, quantify and highlight privacy threats in the internet. Big data, automatic crawling, machine learning are fundamentals building block to detect which private information systems are collecting, how they store and manage the data, if they share data with third parties, etc.
- Personal privacy preserving analytics, as means to impose control on personal data. The candidate will use concepts like Zero Knowledge, Differential Privacy, K-Anonymity to achieve the goal to design and engineer solutions that allow one to share their data, while keeping control on it.
- Automatic collection and computation of easy to understand novel privacy metrics. The candidate will have to design easy to understand metrics that allows anyone to understand the privacy threat when accessing an online service – a fundamental information for a user to know to take informed decisions.
How to apply:
Interested candidates can contact the Prof. Marco Mellia at mellia@polito.it
POST DOC POSITION:
Requirements:
- PhD in Computer Science or equivalent disciplines.
- Strong publication record in top academic conferences and/or journals.
- Background in privacy-preserving and machine learning methodologies.
- Knowledge of big data tools for data science.
Dates:
The starting date is flexible, ideally beginning of 2020.
Appointment:
Post-Doc (assegno di ricerca) duration of 1 year, with funding for renewal up to 3 years, based on mutual interest.
1-Year PostDoc position (Call identifier: AR037/2018)
Department: Dipartimento di Elettronica e Telecomunicazioni (Politecnico di Torino)
Title of the research program: Application of neural networks to big data
Objectives
The Research Program focus on deep neural networks and their applications to large amounts of data, including visual data. Neural networks have become one of the most important tools for data analysis, and the program aims at advancing the state of the art in this field, considering different types of neural networks (feedforward, convolutional, recurrent), as well as generative networks and networks defined on graphs. The Research Program applies neural networks to various kinds of data, including images and videos, biomedical data, point clouds, data coming from industrial sites, just to mention a few.
1-Year PostDoc position (Call identifier: AR052/2018)
Department: Dipartimento di Elettronica e Telecomunicazioni (Politecnico di Torino)
Title of the research program: Big data based Internet Monitoring System with applications to cybersecurity
Objectives
The Research Program focuses on traffic monitoring and anomaly identification in Internet traffic with applications to cybersecurity. A distributed measurement infrastructure to perform active, passive and hybrid measurements; it operates at a wide variety of scales and dynamically supports new functionality. A data lake collects, stores, and analyses the data allowing parallel processing and data mining applications. An Intelligent Reasoner iteratively analyses the data, identifying possible anomalies using Big Data approaches and possible branches of cybersecurity.