From besenbacher at clin.au.dk Mon Jul 15 13:05:47 2024 From: besenbacher at clin.au.dk (=?utf-8?B?U8O4cmVuIEJlc2VuYmFjaGVy?=) Date: Mon, 15 Jul 2024 11:05:47 +0000 Subject: [SocBiN] Bioinformatics/Data Science Postdoc Message-ID: <96780AF8-F3E7-4AE0-B595-189CA070F732@birc.au.dk> I am seeking a Bioinformatics/Data Science postdoc to join my research group at Aarhus University. The job posting and application link can be found here: https://au.career.emply.com/en/ad/genopslag-bioinformatics-data-science-postdoc-analysing-mutation-processes-in-t/irho1i This is a reposting of a previously announced job opening. There are no internal candidates, and I encourage everyone interested in the position to apply. Please email me (besenbacher at clin.au.dk) if you have any questions about the position or the application procedure (uploading a teaching portfolio is not necessary). Best, Søren Besenbacher Associate Professor Department of Molecular Medicine (MOMA) and Bioinformatics Research Centre (BiRC) Aarhus University From arne.elofsson at gmail.com Mon Jul 15 18:17:47 2024 From: arne.elofsson at gmail.com (Arne Elofsson) Date: Mon, 15 Jul 2024 18:17:47 +0200 Subject: [SocBiN] Fwd: Machine Learning Postdoc at Harvard Medical School - Sander Lab In-Reply-To: References: Message-ID: Dear Colleague: perhaps you can forward this to interested recent or imminent PhDs, who may be interested in joining my research group at Harvard Medical School. *Systems Biology at Harvard Medical School - Postdoc position* There is an opportunity for postdocs in data science and machine learning to solve challenging problems: *(1) Catch cancer early using AI* *(2) Develop large-scale predictive models of cell biology* *(3) Design proteins for environmental or therapeutic purposes* July 15, 2024———————————————————————————————————— The ad: *Machine Learning Postdoc at Harvard Medical School* The lab of Chris Sander, in collaboration with Debora Marks, plans to recruit postdocs to work on AI for cancer risk prediction, computational cell biology, and protein design. Join us to develop and apply machine learning and statistical physics methods for impactful research in human disease and synthetic biology. We are in the department of systems biology and collaborate with research groups in the Boston area, including the Ludwig Center, Mass General Hospital and the Broad Institute, and with researchers in the US, Canada, Denmark, Germany, China, and the UK. *Areas of focus:* • *Cancer Risk Prediction:* Use machine learning to identify patients at high risk for aggressive cancers so they can be enrolled in interception programs for prevention, early detection and early-stage treatment. On github: CancerRiskNet. • *Perturbation Biology:* Develop computational models of cell biology from large-scale experiments - link novel perturbations with molecular and phenotypic changes, so as to guide therapeutic developments and cell biological experiments. On github: CellBox, scPerturb. • *Protein Function and Design*: Predict protein function from sequences, design novel proteins for environmental or therapeutic purposes, and collaborate on engineering beneficial gene and protein modules. See for example: bit.ly/betalacdesign *Qualification::* • PhD in biology, medicine, mathematics, computer science, physics, chemistry, or engineering. *Application:* • Send CV, bibliography, statement of research interest (~1 page), and names of 3 references to sander.research #at& gmail.com. Join us for basic and applied research in biological machine learning and data science in Boston, with collaborative international connections. *Sander lab:* Armenise Building, Systems Biology, Harvard Medical School List of publications via Google Scholar By year of publication: http://bit.ly/ACCayl By citation count: http://bit.ly/yAdPhU Key publications: 1 First successful folding and all-atom 3D structures from evolutionary couplings just from sequence information - http://bit.ly/tob48p 2 cBioPortal for Cancer Genomics - knowledge tool for cancer research - DOI: 10.1158/2159-8290.CD-12-0095 3 Protein structure from experimental evolution - bit.ly/3DseqOpen 4 Pancreatic cancer risk predicted from disease trajectories using deep learning – bit.ly/pdacrisk-natmed -------------- next part -------------- An HTML attachment was scrubbed... URL: From prash at bioclues.org Mon Jul 29 16:38:56 2024 From: prash at bioclues.org (Prash) Date: Mon, 29 Jul 2024 20:08:56 +0530 Subject: [SocBiN] Call for Nominations of the Bioclues Innovation, Research and Development (BIRD) awards for the year 2024. Message-ID: Call for Nominations of the Bioclues Innovation, Research and Development (BIRD) awards for the year 2024. ************************************************************************************** To encourage bioinformaticists in India who have made outstanding contributions in the area of Bioinformatics and Functional Genomics, we have initiated the BIRD awards in 2011. This award is meant not just for academicians but also for scientists who have shown exemplary excellence in the field of Bioinformatics. While scientists who have been working for not-for-profit organizations will be given importance, the ones who are working for commercial organisations are no less exceptional if the research they have carried out has been widely honoured and have made longstanding contributions. The awardee would receive a plaque and a citation with certificate. The awardee would further be invited to join the Bioclues executive team (BET) of Bioclues society. More at https://bioclues.org/bird-awards/ -- Prashanth N Suravajhala, Ph.D. Principal Scientist, Systems Genomics Lab # 210, Amrita School of Biotechnology Amrita University, Amritapuri, Kerala 690525, India. Group page: http://www.bioinformatics.org/wiki/Prash E mail: prashATamDOTamritaDOTedu Twitter: @prashbio "One rule is important in science- only courageous people win " ~ Max Planck -------------- next part -------------- An HTML attachment was scrubbed... URL: