Positions available at IIT-CNR, Pisa, Italy - Postdoc and Research Assistant

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Research positions are open @ IIT-CNR, Pisa, Italy, on the following topics:

#1: Big Data Analysis and Decision Support Systems for Smart Healthcare applications
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** Position type: Research Assistant, 12 months
** Scientific Supervisor: Franca Delmastro - https://www.iit.cnr.it/franca.delmastro/
https://scholar.google.it/citations?hl=it&user=fiw73vIAAAAJ
** Net salary: ~ EUR 1500 per month
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#2: Cooperative Ubiquitous Opportunistic Charging with Intelligent Battery Aging Mitigation
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** Position type: Postdoctoral Fellowship, 12 months
** Scientific Supervisor: Theofanis Raptis - https://www.iit.cnr.it/theofanis.raptis/
https://scholar.google.com/citations?user=aDoDo_kAAAAJ&hl=en
** Net salary: ~ EUR 1625 per month
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** Starting date: Q2 2021
** Location: Ubiquitous Internet Research Unit (RU) @ IIT-CNR, Pisa, Italy - http://www.iit.cnr.it/
** RU Leader: Andrea Passarella - https://scholar.google.it/citations?user=sesKnygAAAAJ&hl=it
** Application deadline: continuous evaluation, up until March 31, 2021

Position #1: Big Data Analysis and Decision Support Systems for Smart Healthcare applications
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Job description
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Smart Healthcare applications represent today a hot research field, including remote health monitoring solutions enriched with AI algorithms for the automatic detection and prediction of risky and adverse health conditions of specific user categories (e.g., frail older adults, subjects affected by chronic diseases). To this aim, data derived from IoT systems are enriched with sensing data derived from personal and wearable devices in order to provide a complete picture of the user's health status, including physical, cognitive and social conditions, on a long-term period.

A research assistant position is open in this area for the definition and evaluation of AI algorithms for anomalous behaviour detection and risk prediction both in specific health domains (mainly nutrition, sleep disorders, and stress conditions) and integrated in a multidimensional evaluation of frailty condition in older adults. These algorithms should also be designed to be integrated in a mobile health (m-health) solution to guarantee the processing of sensitive data directly on the personal mobile device and to provide a personalised and motivational feedback to the monitored subject. The algorithms will be validated both on available datasets and on new datasets collected through the application of prototype solutions in real scenarios and pilot studies based on the collaboration with medical units.

The Research assistant will work on the following topics:
(i) Design and evaluation of AI algorithms for anomalous behaviour detection and risk prediction based on heterogeneous sensing data.
(ii) Integration of the proposed algorithms in a prototype m-health application.
(iii) Participation in the definition and deployment of pilot studies with real subjects.

Candidate profile
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Candidates should have a MSc degree in Computer Science, Computer Engineering, or closely related disciplines, and a proven track record of excellent University grades. Preferably, the topic of the MSc thesis should be in one of the relevant research areas (Artificial Intelligence, BigData analytics, distributed systems, e-health applications).
Good written and spoken communication skills in English are required.

The selected candidate could also be interested in applying to a PhD program in Fall 2021.

Specifically, IIT-CNR is part of several PhD programs including:
- the PhD program in Data Science (https://datasciencephd.eu/) hosted by the Scuola Normale Superiore (https://www.sns.it/en)
- the PhD programs in Computer Engineering (https://phd.dii.unipi.it/en/) and Computer Science (https://dottorato.di.unipi.it/), hosted by the University of Pisa
- the PhD program in Smart Computing, jointly organised by the Universities of Florence, Pisa, Siena, CNR, FBK (https://smartcomputing.unifi.it/)

The selection for PhD programs is managed by the related hosting university and applicants will apply directly to the official call of the specific PhD.

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Position #2: Cooperative Ubiquitous Opportunistic Charging with Intelligent Battery Aging Mitigation
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Job description
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Battery aging (the loss of battery's capacity and internal resistance growth) is an emerging challenge for portable devices carried by mobile users. Due to the fact that newer devices are becoming more feature-rich and resource demanding, they are subjected to more charge-discharge cycles compared to their older counterparts; a pattern which increases their battery aging, and enables them to require higher power and more expensive and bigger batteries. Individualized battery aging mitigation and user profiling, which do not take into account neither other users in the networked population nor emerging energy sharing technologies like peer-to-peer wireless power transfer, are not uncovering the full potential of intelligent charging.

One post-doc position is open in this area, for the design and deployment of ubiquitous charging intelligence in order to cooperatively mitigate battery aging, radically optimize energy redistributions, and unorthodoxically increase user quality of experience. The envisioned approach will deliver fine-grained modelling and algorithmic exploitation of not only static wired charging but also wireless energy sharing technologies, and will provide a novel combination of theoretical tools, socio-technical extensions, practical simulations and (potentially) limited field trials.

The Postdoctoral Fellow will work on the following topics:
(i) Rigorous socio-technical modelling for populations of cooperative mobile users
(ii) Algorithmic development for intelligent, network-wide, wired/wireless charging with battery aging mitigation
(iii) Performance evaluation through large scale simulations and/or real device experimentation

Candidate profile
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Ideal candidates should have (or are about to obtain) a PhD in Computer Science, Computer Engineering, or closely related disciplines, and a proven track record of publications in relevant top-tier journals and conferences. Preferably, the topic of the PhD should have been in one of the related research areas (mobile computing, WSNs, opportunistic networks, IoT). Good written and spoken communication skills in English are required.

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Research Unit (RU)
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The positions will be in the Ubiquitous Internet (UI) RU of IIT-CNR in Pisa, Italy (http://cnd.iit.cnr.it). UI activities range over multiple topics related to the design and analysis of the Next Generation Internet networking and computing systems, including edge computing, Internet of People, decentralised AI, human-centric networked systems, online/mobile social networks, data centric and self-organising networks. Verticals of interest include Industry 4.0, e-health, energy efficiency, smart mobility. The RU has a strong track record of successful activities in national and European projects, from FP6 to H2020, which is reflected in the many international collaborations in EU and USA activated by the researchers of the RU.

Application procedure
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Applications should consist of (all documents in English):
- a complete CV
- a 1-page research statement showing motivation, understanding and knowledge on the topic of the position
- contact details of 1-2 persons who could act as reference(s)

The applications and any request of information should be sent to:
** Position #1: franca.delmastro@iit.cnr.it with subject "Research assistant application: smart healthcare"
** Position #2: theofanis.raptis@iit.cnr.it with subject "Post-doc application: cuochi.bam"

Applications will be continuously evaluated upon reception. Interviews will be organized with selected candidates. Applications will be considered until the position is filled, up until March, 31 2021.

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