September 2015 - Comp-neuro - lists.cnsorg.org

Postdoc

by Pestilli, Franco

Dear Community, We are looking for a talented individual to work on a large-scale neuroimaging project funded by the Indiana CTSI<https://www.indianactsi.org/>. The project aims at applying cutting-edge neuroimaging and connectomics methods (Pestilli et al., Nature Methods 2014<http://www.nature.com/nmeth/journal/v11/n10/abs/nmeth.3098.html>; Mišić et al., Neuron 2015<http://www.cell.com/neuron/abstract/S0896-6273(15)00474-2>) on the latest generation of data from Indiana Alzheimer Disease Center<http://iadc.medicine.iu.edu/>. The project is a collaboration between groups at Indiana <https://www.indiana.edu/> University Bloomington<https://www.indiana.edu/> (Franco Pestilli and Olaf Sporns), Indiana University School of Medicine, Indianapolis (Andrew Saykin, Li Shen, and Yu-Chien, Wu) and Purdue University, Lafayette (Joaquin Goñi). The team has strong expertise in aging and Alzheimer’s disease, imaging genetics, network science, magnetic resonance imaging measurements and computational modeling. The ideal candidate will have a PhD in Computer Science, Engineering, Neuroscience, Informatics or Cognitive Science. Strong programming skills (e.g., in Python, MATLAB, or C/C++) and previous background in neuroimaging, computational modeling, or machine learning will be highly valued. The project will involve developing and publishing software products as well as contributing to ongoing software projects such as: https://francopestilli.github.io/life and https://sites.google.com/site/bctnet/. Preference will be given to candidates demonstrating successful productivity by means of scientific articles and software publishing. Interested candidates should send CV, statement of research interests, and names of three references to Dr. Franco Pestilli franpest(a)indiana.edu<mailto:franpest@indiana.edu>. Review of the applications will start immediately and continue until the position is filled. Dr. Pestilli and Professor Sporns will be available at SfN in Chicago for informal meetings with potential candidates. Indiana University is an equal employment and affirmative action employer and a provider of ADA services. All qualified applicants will receive consideration for employment without regard to age, ethnicity, color, race, religion, sex, sexual orientation or identity, national origin, national origin, disability status or protected veteran status. Best regards, Franco Franco Pestilli, PhD Assistant Professor Psychology<http://psych.indiana.edu/>, Neuroscience<http://www.indiana.edu/~neurosci/> and Cognitive Science<http://www.cogs.indiana.edu/> Indiana Network Science Institute<http://iuni.iu.edu/> 𝞇 Indiana University, Bloomington<http://www.iub.edu/>, IN 47405<http://goo.gl/0uVOc8> francopestilli.com<http://www.francopestilli.com/> | franpest(a)indiana.edu<mailto:franpest@indiana.edu> Phone: +1 (812) 856 9967

Sept. 1, 2015

open positions in machine learning and computational neuroscience

by Turaga, Srinivas C

The Turaga Lab is looking for exceptional postdoctoral researchers and programmers (and graduate students!) for research at the intersection of machine learning and neuroscience. https://www.janelia.org/lab/turaga-lab With recent technological advances in 3d electron microscopy, optogenetics and large-scale chronic in vivo neural imaging, it is now possible to measure and perturb the activity of large populations of neurons, and to map their connectivity. These new data can be used understand how the structure of a neural circuit gives rise to its function. Our lab develops machine learning algorithms to map neural connectivity, and statistical models to characterize neural activity and to relate activity to connectivity. We have pioneered the use of deep-learning based machine learning algorithms to map neural connectivity from 3d electron microscopic images of brain tissue, and we are now working to improve these methods. This involves solving interesting new problems in structured prediction, active learning and unsupervised learning at an unprecedented scale (imagine working with labeled training datasets with 10^9 examples in a 10^6 dimensional feature space and wanting to achieve accuracies of 99.999%!). We are also developing novel statistical methods to analyze large-scale calcium imaging datasets. This is with an eye towards combining such large-scale activity measurements with structural connectomes in order to relate neural activity to neural connectivity with statistical and mechanistic models. HHMI's Janelia Research Campus is a unique, world-class research community near Washington, D.C. dedicated to understanding the function of neural circuits and developing synergistic imaging technology. Our highly collaborative structure is designed to support interdisciplinary work in small lab groups. We seek candidates who are comfortable with risk and are able to think independently to develop novel approaches. Applicants should have a strong quantitative background with degrees or expertise in machine learning, computational neuroscience, applied mathematics, physics or related discipline. Excellent collaborative programming skills in Python, C/C++, Java or similar languages are essential. To apply, please send a CV and names and addresses of 2-3 references by email to Dr. Srini Turaga, turagas(a)janelia.hhmi.org.

Sept. 1, 2015

SFN 2015 Workshop: high performance computing via Neuroscience Gateway

by Ted Carnevale

What: Workshop on the Neuroscience Gateway Portal (NSG, http://www.nsgportal.org) When: 9AM - Noon on Saturday, October 17, 2015. Registration deadline: Friday, October 2, 2015. Where: Downtown Chicago (exact location announced to registrants) Speakers: Amit Majumdar, Subha Sivagnanam, Padraig Gleeson, Simon Rothmeier, Ted Carnevale, Alex Peyser, Hannah Bos. Agenda: Downloadable from http://www.nsgportal.org/workshop.html Why: If you have, or plan to start, a research project that involves computationally intensive modeling or data analysis, you should know about NSG. NSG is being developed with support from NSF to make it easy for neuroscientists to use high performance computing (HPC) resources in their research. Some of NSG's advantages: * Quick and easy account application and approval. * Free computing time. No cost to your account budget! * Simple user interface for uploading data, running simulations or data analysis tasks, and downloading results * Installed software includes MOOSE, GENESIS 3, NEST, NEURON, PyNN, the Freesurfer Software Suite, and the Virtual Brain Empirical Data Pipeline For more information or to sign up, see http://www.neuron.yale.edu/neuron/static/courses/nsg2015/nsg2015.html or contact Ted Carnevale [ted dot carnevale at yale dot edu] or Amit Majumdar [majumdar at sdsc dot edu]

Sept. 1, 2015