[Job-offers-cs] Research Assistant and Postdoc positions available at IIT-CNR, Pisa, Italy

[Pekka Orponen]

-------- Forwarded Message --------
Subject: [DMANET] Research Assistant and Postdoc positions available at 
IIT-CNR, Pisa, Italy
Date: Thu, 7 Jan 2021 14:51:18 +0100
From: Theofanis Raptis <theofanis.raptis at iit.cnr.it>
To: dmanet at zpr.uni-koeln.de

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

#1: Big Data Analysis and Decision Support Systems for Smart Healthcare 
applications
==========================================================
** Position type: Research Assistant, 12 months
** Scientific Supervisor: Franca Delmastro - 
https://www.iit.cnr.it/franca.delmastro/
https://scholar.google.it/citations?user=fiw73vIAAAAJ
** Net salary: ~ EUR 1500 per month
==========================================================

#2: Cooperative Ubiquitous Opportunistic Charging with Intelligent 
Battery Aging Mitigation
==========================================================
** 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
** Net salary: ~ EUR 1625 per month
==========================================================

** Starting date: Q1 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
** Application deadline: continuous evaluation, up until mid-February 2021




Position #1: Big Data Analysis and Decision Support Systems for Smart 
Healthcare applications
==========================================================

Job description
---------------
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
---------------
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.

==========================================================



Position #2: Cooperative Ubiquitous Opportunistic Charging with 
Intelligent Battery Aging Mitigation
==========================================================

Job description
---------------
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
---------------
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.

==========================================================



Research Unit (RU)
---------------
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
---------------
Applications should consist of (all documents in English):
- a complete CV, with a complete transcript of the university grades, 
both at the MSc and PhD levels
- 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 at iit.cnr.it with subject "Research 
assistant application: smart healthcare”
** Position #2: theofanis.raptis at 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 suitable candidates are identified up to mid-February 
2021. Interested candidates are thus strongly encouraged to send their 
application as soon as possible.