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<p><b>Call for Post-degree or Post-doc Position</b><br>
</p>
<p>We are pleased to announce a Post-degree or Post-doc Position
(m/f/d) in the field Machine and Deep Learning at the <b>M.O.D.A.L.
– Mathematical mOdelling and Data AnaLysis</b> research group,
University of Naples Federico II, Italy,
<a class="moz-txt-link-freetext" href="http://www.labdma.unina.it">http://www.labdma.unina.it</a><br>
<br>
The position is funded by CENTRO NAZIONALE HPC, BIG DATA E QUANTUM
COMPUTING ITALIAN CENTER FOR SUPER COMPUTING (ICSC) – SPOKE 9",
CUP: E63C22000980007 – PNRR</p>
<p>The main objective of the research activity will be the design
and application of advanced Machine Learning and Deep Learning
methodologies for data analysis in the context of a Smart City and
Digital Society. The aim is to develop predictive models and
intelligent systems capable of extracting meaningful information
from the data collected within a Smart City, enabling optimized
resource management, improving the quality of life for citizens,
and promoting a more effective and sustainable digital society.<br>
</p>
<p>The position is available immediately; the official opening
announcement will be online in the coming days, with a deadline
(for the application submission) of October 17th, and the start of
employment on November 1st, 2023.<br>
</p>
<p>To receive additional details you are kindly invited to contact
in advance Francesco Piccialli (<a class="moz-txt-link-abbreviated" href="mailto:francesco.piccialli@unina.it">francesco.piccialli@unina.it</a>)<br>
</p>
<p><b>Your tasks at a glance</b><br>
• Performing cutting edge research on Machine and Deep Learning
methodologies for Smart City<br>
• Working on the project, especially planning, implementing and
executing research<br>
• Conduct and participate in research projects such as lab and
equipment set up, data collection, data analysis,<br>
• Participate in routine laboratory operations, such as
planning and preparations for experiments, lab maintenance and lab
procedures.<br>
• Coordinate with the PI and other team members for strategies
and project planning.<br>
</p>
<p><b>Your qualifications and competences</b><br>
• Completed Master’s or equivalent university degree in
Computers Science, Mathematics, Computer Engineering, Mathematical
Engineering;<br>
• Skills in Python, Tensorflow, Pytorch are an advantage ;<br>
• Interest in fundamental research and experimental work ;<br>
• Skills in Machine and Deep Learning;<br>
• International experience is another advantage ;<br>
• Very good English skills;<br>
</p>
<p><b>Who we Are</b><br>
M.O.D.A.L. – Mathematical mOdelling and Data AnaLysis research
group – <a class="moz-txt-link-freetext" href="https://www.labdma.unina.it">https://www.labdma.unina.it</a><br>
</p>
<p><b>Contacts</b><br>
<a class="moz-txt-link-abbreviated" href="mailto:francesco.piccialli@unina.it">francesco.piccialli@unina.it</a> -
<a class="moz-txt-link-freetext" href="http://wpage.unina.it/francesco.piccialli/">http://wpage.unina.it/francesco.piccialli/</a><br>
<br>
</p>
<pre class="moz-signature" cols="72">--
Prof. Francesco Piccialli, Ph.D.
DMA - Department of Mathematics and Applications "R. Caccioppoli"
University of Naples Federico II, Italy
Tel. +39 081675787
Web: <a class="moz-txt-link-freetext" href="http://wpage.unina.it/francesco.piccialli/">http://wpage.unina.it/francesco.piccialli/</a>
Google Scholar: <a class="moz-txt-link-freetext" href="https://scholar.google.it/citations?user=CLNn_9gAAAAJ&hl=it">https://scholar.google.it/citations?user=CLNn_9gAAAAJ&hl=it</a>
M.O.D.A.L group: <a class="moz-txt-link-freetext" href="https://www.labdma.unina.it">https://www.labdma.unina.it</a>
Institutional web: <a class="moz-txt-link-freetext" href="https://www.docenti.unina.it/francesco.piccialli">https://www.docenti.unina.it/francesco.piccialli</a></pre>
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