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<p>The Lab of Robert Legenstein at Graz University of Technology
(Austria) is offering a funded PhD position in the areas Spiking
Neural Networks/Machine Learning/Brain Models/Neuromorphic
Hardware. A background in Machine Learning, Computer Science, or
Mathematics is desirable, as well as evidence for excellent prior
performance as a student. <br>
<br>
The successful candidate will work on learning algorithms for
spiking neural networks in the international consortium of the
international project "Scalable Learning Neuromorphics". We will
develop in this project learning algorithms for spiking neural
networks for memristive hardware implementations. <br>
<br>
Please send your application including a CV, any prior thesis
and/or work by October 20 to <br>
<a class="moz-txt-link-abbreviated moz-txt-link-freetext"
href="mailto:robert.legenstein@igi.tugraz.at">robert.legenstein@igi.tugraz.at</a></p>
<p>Scalable Learning Neuromorphics project description:</p>
<p dir="ltr" style="line-height: 1.56; margin-top: 0pt;
margin-bottom: 0pt;" align="left"><span style="font-size:12pt;font-family:'Open Sans';color:#212121ff;background-color:transparent;font-weight:400;font-style:italic;font-variant:normal;text-decoration:none;vertical-align:baseline;white-space:pre;white-space:pre-wrap;">This project aims to develop scalable Spiking Neural Networks (SNNs) by leveraging the integration of 3D memristors, thereby overcoming limitations of conventional Artificial Neural Networks (ANNs). Positioned at the intersection of artificial intelligence and brain-inspired computing, the initiative focuses on innovative SNN training methods, optimizing recurrent connections, and designing dedicated hardware accelerators. These advancements will uniquely contribute to scalability and energy efficiency. The endeavor addresses key challenges in event-based processing and temporal coding, aiming for substantial performance gains in both software and hardware implementations of artificial intelligence systems. Expected research outputs include novel algorithms, optimization methods, and memristor-based hardware architectures, with broad applications and potential for technology transfer.</span></p>
<p></p>
<pre class="moz-signature" cols="72">--
Dr. Robert Legenstein
Univ.-Professor
Institute of Theoretical Computer Science
Graz University of Technology
Inffeldgasse 16b/I, 8010 Graz, Austria
<a class="moz-txt-link-freetext" href="http://www.igi.tugraz.at/legi/">http://www.igi.tugraz.at/legi/</a>
Follow @CompLegenstein on Twitter.
++43/316/873-5824
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