UH Biocomputation Group - Human Brain Projecthttp://biocomputation.herts.ac.uk/2017-04-25T17:08:31+01:00Open Position: Postdoc in neuromorphic pattern recognition2017-04-25T17:08:31+01:002017-04-25T17:08:31+01:00Michael Schmukertag:biocomputation.herts.ac.uk,2017-04-25:/2017/04/25/open-position-postdoc-in-neuromorphic-pattern-recognition.html<p class="first last">Applications are invited for a postdoc position in the Biocomputation group, at the University of Hertfordshire, UK. The appointment is due to start as soon as possible. Please apply online via <a class="reference external" href="http://jobs.herts.ac.uk">http://jobs.herts.ac.uk</a>, vacancy reference 014592, until 22nd May, 2017 at the latest. More details within.</p>
<p>Applications are invited for a postdoc position in the Biocomputation group at the <a class="reference external" href="http://www.herts.ac.uk/">University of Hertfordshire</a>, UK. The appointment is due to start as soon as possible, with an initial fixed duration until 31st March 2018, with a possibility to extend, pending funding decisions.</p>
<p>The successful candidate will join our efforts to advance neuromorphic pattern recognition on the <a class="reference external" href="http://apt.cs.manchester.ac.uk/projects/SpiNNaker/">SpiNNaker</a> and <a class="reference external" href="http://brainscales.kip.uni-heidelberg.de/public/">BrainScaleS</a> hardware systems that are built within the <a class="reference external" href="https://www.humanbrainproject.eu/en/">Human Brain Project (HBP)</a>. We are looking for a candidate with a keen tenacity in pushing forward the boundaries of future computing off the well-trodden path.</p>
<p>The Biocomputation group provides a rich and inspiring interdisciplinary research environment that connects Computer Science with Neuroscience and branches out into Machine Learning and Robotics.</p>
<p>HBP membership provides excellent opportunities to connect to world-leading scientists in all aspects of neuroscience, high-performance computing, neurorobotics and neuromorphic engineering. We enjoy first-class access to the latest neuromorphic technologies developed in HBP, and we work in tight interaction with the groups developing the hardware systems, <a class="reference external" href="http://apt.cs.manchester.ac.uk/projects/SpiNNaker/">SpiNNaker</a> and <a class="reference external" href="http://brainscales.kip.uni-heidelberg.de/public/">BrainScaleS</a>.</p>
<p>Research in Computer Science at the University of Hertfordshire has been recognized as excellent in the REF 2014, with 50% of the research submitted rated as internationally excellent or world leading. The University is situated in Hatfield, in the green belt just north of London.</p>
<p>Candidates should have a PhD in neuromorphic computing, machine learning, computational neuroscience, computer science, physics or another relevant subject area. In addition, the successful candidate should have demonstrable experience in either:</p>
<ul class="simple">
<li>Machine learning and pattern recognition, ideally deep and recurrent neural networks, self-organisation, or</li>
<li>Neuromorphic computing, ideally with hands-on experience with <a class="reference external" href="http://apt.cs.manchester.ac.uk/projects/SpiNNaker/">SpiNNaker</a>, <a class="reference external" href="http://brainscales.kip.uni-heidelberg.de/public/">BrainScaleS</a>, or other neuromorphic hardware systems, or GPU-accelerated simulations.</li>
</ul>
<p>Further desired skills:</p>
<ul class="simple">
<li>Ability to conduct original research, as evidenced by high-quality, peer-reviewed papers,</li>
<li>Excellent programming skills, as evidenced e.g. by a link to a github account that shows work on relevant projects,</li>
<li>Ability to work and communicate in a multidisciplinary team.</li>
</ul>
<p>Informal inquiries about this post are warmly welcome and should be directed to Dr Michael Schmuker, <code>m.schmuker AT herts DOT ac DOT uk</code>.</p>
<p>Please apply online via <a class="reference external" href="http://jobs.herts.ac.uk">http://jobs.herts.ac.uk</a>, vacancy reference 014592, until 22nd May, 2017 at the latest.</p>
Capturing dendritic computation with the Green’s function formalism2016-01-06T14:44:56+00:002016-01-06T14:44:56+00:00Willem Wybotag:biocomputation.herts.ac.uk,2016-01-06:/2016/01/06/capturing-dendritic-computation-with-the-green-s-function-formalism.html<p class="first last">Special journal club session - Willem Wybo from the Human Brain Project at EPFL will speak about his work on enhancing the Green's function formalism to study neuronal integration, dendritic compartmentalization and interactions between synaptic inputs.</p>
<p>Neurons are spatially extended structures with an elaborate dendritic tree that integrates spatio-temporal input patterns. To model this integration, researchers have relied on compartmental simulations of the cable equation, where space is discretized in many equipotential compartments. However, this approach is computationally expensive and obfuscates the interactions among distant synapses .</p>
<p>The Green's function (GF) formalism can potentially solve these issues: it is conceptually simple, as the complicated spatio-temporal interactions are captured in a system of temporal kernels, and provides a simulation paradigm that scales independently of the morphological complexity. However, the computational cost scales quadratically in the number of inputs. Historically, the GF formalism was abandoned because of this reason, along with the fact that it required computationally costly convolutions and the belief that is was restricted to linear membranes.</p>
<p>In this talk, I will show how all aforementioned pitfalls can be circumvented. First, I will outline how the system can be transformed so that it scales linearly in the number of input locations. Second, I will show that convolutions can be re-expressed as simple differential equations. Third, I will discuss the inclusion of non-linear membrane currents and related, how this 'sparsified' GF formalism reduces to the canonically used 2nd order finite difference approximation.</p>
<p>I will also briefly outline how this new simulation algorithm for neurons can be implemented and discuss possible use cases in which computational advantage over the classic methods is expected.</p>
<p><strong>Date:</strong> 15/01/2016 <br />
<strong>Time:</strong> 16:00 <br />
<strong>Location</strong>: LB252</p>
Reconstruction and simulation of neocortical microcircuitry2015-11-05T09:38:27+00:002015-11-05T09:38:27+00:00Benjamin Torben-Nielsentag:biocomputation.herts.ac.uk,2015-11-05:/2015/11/05/reconstruction-and-simulation-of-neocortical-microcircuitry.html<p class="first last">Benjamin Torben-Nielsen's journal club session on the Blue Brain Project's recent model of the rat cortex.</p>
<p>In 2013, the <a class="reference external" href="https://www.humanbrainproject.eu/en_GB">Human Brain Project</a> was awarded one out of two European FET flagship grants worth 1.2 billion Euros over the next ten years. Recently, the HBP’s predecessor, the <a class="reference external" href="http://bluebrain.epfl.ch/">Blue Brain Project</a> published a <a class="reference external" href="http://www.cell.com/abstract/S0092-8674(15)01191-5">first-draft model of a small piece of rat cortex</a> . A staggering 13 companion papers were published at roughly the same time disclosing details about the model construction pipeline, the algorithms used and dedicated software to built and disseminate the model. The reported simulations indicate a high degree of accuracy in replicating in vitro and in vivo (rat) brain dynamics.</p>
<p>I would like to highlight some parts of the model and selected results. Then, I will discuss what this type of results can tell us. Specifically, I want to address incredible flexibility of the brain (because a simulation without several crucial components can still replicate brain dynamics) or, our grotesque misunderstanding of the brain (because a simulation without crucial components appears to replicate brain dynamics).</p>
<p><strong>Date:</strong> 06/11/2015 <br />
<strong>Time:</strong> 16:00 <br />
<strong>Location</strong>: LB252</p>