From owner-chemistry@ccl.net Mon Apr 18 13:06:01 2016 From: "Gunther Stahl gunther.stahl.[a].eyesopen.com" To: CCL Subject: CCL: OpenEye's Scientific European Meeting - Student bursaries available Message-Id: <-52144-160418122433-28955-OxSFE5naexhOkHXaGVmpGA[a]server.ccl.net> X-Original-From: "Gunther Stahl" Date: Mon, 18 Apr 2016 12:24:32 -0400 Sent to CCL by: "Gunther Stahl" [gunther.stahl],[eyesopen.com] OpenEye is pleased to announce its annual European Scientific Conference and User Group Meeting EuroCUP IX EuroCUP IX will be taking place at the Chateau De La Begude in Nice, France > from June 15-17, 2016. The format will be much the same as in previous years, with 4 half-day sessions across the 3 days. The Wednesday afternoon is set aside for presentations from OpenEye, while Thursday and Friday will feature talks by speakers from industry and academia. There will be a poster session on Wednesday night. Everyone is encouraged to present a poster. OpenEye is awarding several travel grants (covering the cost of accommodation and board) to students presenting a poster. To apply, please register on the website and provide your proposed topic. Registration for EuroCUP is free except for accommodation and board costs which need to be paid to the hotel. For more information please check: http://www.eyesopen.com/events/eurocup-ix From owner-chemistry@ccl.net Mon Apr 18 20:44:01 2016 From: "Dan Pope daniel.j.pope[-]wsu.edu" To: CCL Subject: CCL: Changing cpuspercore setting in Materials Studio Message-Id: <-52145-160418183607-6023-AD+72hwJKfCiktyz1NIfmw{:}server.ccl.net> X-Original-From: "Dan Pope" Date: Mon, 18 Apr 2016 18:36:06 -0400 Sent to CCL by: "Dan Pope" [daniel.j.pope^^^wsu.edu] For Materials Studio 8.0 on a Linux cluster, were trying to change the default setting for the number of cores per CPU. It seems that the only way to do this is through accessing the gateway through remote view in the server console or through a URL and changing the setting from there. Is there a way to change this setting from the command line in Linux? From owner-chemistry@ccl.net Mon Apr 18 23:14:00 2016 From: "Johannes Hachmann hachmann_+_buffalo.edu" To: CCL Subject: CCL: Data Mining and Machine Learning in Molecular Sciences at AIChE Message-Id: <-52146-160418230554-9421-Q3DJDvnxsJ/BQifBXWMiSA|,|server.ccl.net> X-Original-From: "Johannes Hachmann" Date: Mon, 18 Apr 2016 23:05:52 -0400 Sent to CCL by: "Johannes Hachmann" [hachmann(~)buffalo.edu] Dear Colleagues, We are writing today to let you know that we will again be running the CoMSEF technical session "Data Mining and Machine Learning in Molecular Sciences" at the 2016 AIChE Annual Meeting in San Francisco (Nov 13-18). Last year's inaugural edition proved to be exceedingly popular and well-attended, indicative of a critical groundswell of excitement and interest within the ChemE community for data-driven methods and applications in the physical, chemical, materials, and life sciences. We are also delighted to announce that this year's session will be anchored by two invited talks from Yannis Kevrekidis (Princeton) and Kristin Persson (Lawrence Berkeley National Lab). We are currently soliciting abstracts for contributed talks, and if you or your students are interested in presenting in this session we would be excited to receive your submission through the online application portal. The scope of the session is intentionally broad, concerning the generic applications of data mining and machine learning for property prediction, molecular understanding, and rational design. Details of the session scope and instructions for abstract submission are provided below. The submission deadline is Monday, May 9. We look forward to seeing you in San Francisco! Kind Regards, Andrew Ferguson (University of Illinois, alf],[illinois.edu) Johannes Hachmann (University at Buffalo, hachmann],[buffalo.edu) --- Data Mining and Machine Learning in Molecular Sciences https://aiche.confex.com/aiche/2016/webprogrampreliminary/Session32684.html Computational approaches to correlate, analyze, and understand large and complex data sets are playing increasingly important roles in the physical, chemical, and life sciences. This session solicits submissions pertaining to methodological advances and applications of data mining and machine learning methods, with particular emphasis on data-driven modeling and property prediction, statistical inference, big data, and informatics. Topics of interest include: algorithm development, inverse engineering, chemical property prediction, genomics/proteomics/metabolomics, (virtual) high-throughput screening, rational design, accelerated simulation, biomolecular folding, reaction networks, and quantum chemistry. 1. Go to https://aiche.confex.com/aiche/2016/cfp.cgi 2. Click on the blue drop down for "Computational Molecular Science and Engineering Forum", and click "Begin a Submission" 3. Select "21004 Data Mining and Machine Learning in Molecular Sciences and then click Save and Continue". ----------------------------------------------------------------------------------------- Dr. Johannes Hachmann Assistant Professor University at Buffalo, The State University of New York Department of Chemical and Biological Engineering (CBE) New York State Center of Excellence in Materials Informatics (CMI) Computational and Data-Enabled Science and Engineering Program (CDSE) 612 Furnas Hall Buffalo, NY 14260 www.cbe.buffalo.edu/hachmann http://hachmannlab.cbe.buffalo.edu -----------------------------------------------------------------------------------------