Saturday, July 9, 2016

dmanet Digest, Vol 101, Issue 8

Send dmanet mailing list submissions to
dmanet@zpr.uni-koeln.de

To subscribe or unsubscribe via the World Wide Web, visit
http://www.zaik.uni-koeln.de/mailman/listinfo/dmanet
or, via email, send a message with subject or body 'help' to
dmanet-request@zpr.uni-koeln.de

You can reach the person managing the list at
dmanet-owner@zpr.uni-koeln.de

When replying, please edit your Subject line so it is more specific
than "Re: Contents of dmanet digest..."


Today's Topics:

1. Funded positions for doctoral research in Algorithmic Game
Theory at Teesside University, UK (Carmine Ventre)
2. Two post-doc positions @ IIT-CNR, Pisa, Italy: OSN analysis &
Fog/Edge computing (Andrea Passarella)


----------------------------------------------------------------------

Message: 1
Date: Fri, 8 Jul 2016 10:27:51 +0100
From: Carmine Ventre <carmine.ventre@gmail.com>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] Funded positions for doctoral research in
Algorithmic Game Theory at Teesside University, UK
Message-ID:
<CAEg4AOVWXJx2OpGF1uYWf2-A2-h4-X3BgiA1ZUSw-Kf4KkF+Cw@mail.gmail.com>
Content-Type: text/plain; charset=UTF-8

Opportunities to undertake a fully funded PhD program in Algorithmic
Game Theory are available at Teesside University, UK.

A first route is via a graduate tutor position. This role allows to
study for a PhD program over 4 years, whilst also gaining the
opportunity to acquire regular and structured experience through a
light contribution to the teaching activities of the School of
Computing. The salary is higher than a normal PhD studentship (and
additionally all fees are paid).

We now accept applications to this role; deadline is July 31, 2016.

More details, including application procedure, can be found at
https://recruitment.tees.ac.uk/itrentlive_webrecruitment/wrd/run/etrec107gf.open?VACANCY_ID=5166081sUE&WVID=3395700LFi&LANG=USA.

Moreover, we anticipate the possibility of having a fully-funded PhD
studentship (without teaching commitments) at a later stage
(presumably after the summer).

Prospective candidates for either role must have (or expect to have)
at least a good honours degree Computer Science, Mathematics or
Economics at grade 2:1 (or equivalent) or higher. The role requires
good background knowledge in Theoretical Computer Science, discrete
mathematics related to computer science and algorithm design.
Background knowledge in Microeconomics or Algorithmic Game Theory is
also desirable.

Prospective applicants are welcome to contact myself for informal
enquiries (about the roles and/or the application procedure).

Finally, with similar modalities, we do have other projects in the
general area of game theory; namely, "Evolutionary Mechanism Design"
and "Emergence of Co-operative Behaviour and AI Cognition". Do have a
look at http://www.tees.ac.uk/sections/research/projects2.cfm and feel
free to contact me for further info on those projects as well.

------------------------------

Message: 2
Date: Fri, 8 Jul 2016 12:32:20 +0200
From: Andrea Passarella <a.passarella@iit.cnr.it>
To: dmanet@zpr.uni-koeln.de
Subject: [DMANET] Two post-doc positions @ IIT-CNR, Pisa, Italy: OSN
analysis & Fog/Edge computing
Message-ID: <472f4e29-9833-6e42-bd2f-9bc78ee3d82a@iit.cnr.it>
Content-Type: text/plain; charset=utf-8; format=flowed

==========================================================
Two post-doc positions are open @ IIT-CNR, Pisa, Italy:
#1: Analysis of large-scale Online Social Networks (H2020 SoBigData)
#2: Fog/Edge computing in IoT (with application to Industry 4.0) (H2020
AUTOWARE)

** Position type: postdoctoral fellowship, 12 months (renewable)
** Starting date: ASAP, from September 2016
** Location: IIT-CNR, Pisa, Italy - http://www.iit.cnr.it/
** Supervisor: Andrea Passarella - http://cnd.iit.cnr.it/andrea/
** Entry-level salary: EUR 1640-1940 per month (net) depending on experience
** Application deadline: continuous evaluation, up until the end of
August 2016


Position #1: Analysis of large-scale Online Social Networks
-----------------------------------------------------------
Job description
---------------
Online Social Networks are one of the main sources of Big Data to
analyse the
human social behaviour, and design smart human-centric services that exploit
this knowledge. The post-doc activities will be focused on
(i) collecting and analysing large-scale datasets that describe
the structure of human social networks in OSNs, and
(ii) designing radically new data-centric services based on this knowledge.

Successful candidates will be supervised by Dr. Andrea Passarella
(http://cnd.iit.cnr.it/andrea), and will work in the H2020 SoBigData
European
Project, the only EC-funded H2020 Research Infrastructure for the
analysis of
human social behaviour from BigData (http://www.sobigdata.eu/).

The post-doc activities will involve developing interdisciplinary
approaches,
mixing efficient data crawling and collection techniques, large-scale data
analysis, complex network analysis and modelling, knowledge extraction
according
to quantitative models describing the humans' social behaviour, design of
data-centric services in OSN platforms.

Candidate profile
-----------------
Ideal candidates should have or about to obtain a PhD in Computer Science,
Computer Engineering, Physics, Statistics, or closely related
disciplines, and a
proven track record of publications in relevant top-tier conferences and
journals. Preferably, the topic of the PhD should have been in one of the
relevant research areas (BigData analytics, OSN analysis/programming,
Complex
network analysis). Good written and spoken communication skills in
English are
required.


Position #2: Fog/Edge computing in IoT (with application to Industry 4.0)
-------------------------------------------------------------------------
Job description
---------------
The expected amount of data generated by pervasive devices in IoT
environments
calls for fog/edge computing approaches where data management and
analysis is
carried out at the edge of the network.

One post-doc position is open in this area, and on the application of
fog/edge
computing to Industry 4.0 systems, the emerging paradigm for the
Factories of
the Future. Industry 4.0 systems are expected to revolutionise the entire
manufacturing process. They will be entirely data-driven, thanks to tight
integration with IoT and data analytics tools. Data will be dynamically
generated, analysed on the fly, and shared across the various actors and
enterprises in the production value chains and between producers and
consumers.

Successful candidates will be supervised by Dr. Andrea Passarella, and the
activities will be carried out in the H2020 FoF AUTOWARE European
Project, expected to start in September 2016.

The post-doc will work on these topics (in the framework of AUTOWARE)
(i) fog computing solutions applied to industry 4.0 environments;
(ii) design of data management and analysis on mobile edge networks;
(iii) optimisation of data management and communication in industry 4.0
environments.
Both protocol design/evaluation and theoretical approaches are expected
to be
applied.

Candidate profile
-----------------
Ideal candidates should have or 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 conferences and journals.
Preferably, the
topic of the PhD should have been in one of the relevant research areas
(IoT,
mobile networking and computing, cloud computing, BigData management and
analysis). Good written and spoken communication skills in English are
required.


Research group
--------------
The Post-doc will be in the Ubiquitous Internet group of IIT-CNR in
Pisa, Italy
(http://cnd.iit.cnr.it). UI activities range over multiple topics
related to the
design and analysis of Future Internet networking and computing systems,
including data-centric networks, mobile computing, online/mobile social
networks, self-organising networks, hybrid wireless/wired networking and
computing. The UI group has a strong track record of successful
activities in
European projects, from FP6 to H2020, which is reflected in the many
international collaborations in EU and USA activated by the researchers
of the
group.

Application procedure
---------------------
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
- up to 3 contacts persons that could act as references, if needed

The applications and any request of information should be sent to:
a.passarella@iit.cnr.it, with subject, respectively:
"Post-doc application: Online Social Network Analysis", or
"Post-doc application: Fog/Edge computing in IoT".

Applications will be continuously evaluated upon reception.
Interviews will be organised with selected candidates.
Applications will be considered until the position is filled, up until
the end of
August 2016.


Contact point
-------------
For any additional information or clarification, please send a message to
a.passarella@iit.cnr.it


--
Andrea Passarella
--
Institute for Informatics and Telematics (IIT)
National Research Council (CNR)
Via G. Moruzzi, 1 voice: +39 050 315 3269 <tel://+39%20050%20315%203269>
56124 Pisa, Italy fax: +39 050 315 2593 <tel://+39%20050%20315%202593>
@/sip: a.passarella@iit.cnr.it <mailto:a.passarella@iit.cnr.it> mobile:
+39 346 0082 540 <tel://+39%20346%200082%20540>
http://cnd.iit.cnr.it/andrea

========================================================================
Just Published!
V. Arnaboldi, A. Passarella, M. Conti, R.I.M. Dunbar
Online Social Networks: Human Cognitive Constraints in Facebook and
Twitter Personal Graphs
Elsevier, October 2015
http://store.elsevier.com/Online-Social-Networks/Valerio-Arnaboldi/isbn-9780128030233/

------------------------------

Subject: Digest Footer

_______________________________________________
dmanet mailing list
dmanet@zpr.uni-koeln.de
http://www.zaik.uni-koeln.de/mailman/listinfo/dmanet


------------------------------

End of dmanet Digest, Vol 101, Issue 8
**************************************

No comments:

Post a Comment