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Mikhail Spivakov
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An amazingly comprehensive review making a case for network analyses in drug discovery: http://arxiv.org/pdf/1210.0330.pdf.  Great for anyone interested in the topic, no less great for making a case for network analyses to non-specialists. Thanks to Mark Ragan and Vladimir Uversky for highlighting the article on F1000 Prime - otherwise I'd never find it.
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A paper in PLoS Biology makes a good case for the community to publicise  paper preprints, just like it has long been done in quantitative disciplines. I very much agree (except perhaps for a small number of special cases), and our latest preprint is already in arXiv :)
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I rarely post about R packages and have probably never done so at 11pm. So here's an exception: Try data.table if you haven't yet done so. Switching to data.tables has speeded things up for me up to 100-fold compared to using mclapply() with data frames on 32 (!) cores on the very first day of learning this package. The syntax is a bit counterintuitive at times though, mainly because it's so much at odds with classic R, but also because it's somewhat less flexible. But really, it is well worth the trouble - at least for any data beyond 100K rows. Not only saves time, but (compared to mclapply) also electricity.
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We are looking for a computational postdoc to work on the functional genomics of ageing. This is a very exciting, collaborative post with lots of great in-house data to mine! http://www.babraham.ac.uk/opportunities/bf_nd3_c/bf_nd3_c.html
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Stumbled across a really cool MEng project: a London journey planner for Underground and Boris bikes that uses a probabilistic model to predict bikes' availability at a docking station: http://www.doc.ic.ac.uk/teaching/distinguished-projects/2012/r.kaleta.pdf
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Will soon be recruiting a postdoc in regulatory genomics - mainly computational, but with some potential wet-lab possibilities. More details to follow, but please drop me a line if you're interested!
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