permanent position for research on computational statistics and “omics” data

There is an opening at the French agronomy and genetics research centre, INRA, for a permanent research position on the country campus of Joyu-en-Josas, south-west of Paris, with focus on computational statistics (incl. machine-learning) and collaborations on omics data. The deadline is March 4. (The procedure is somewhat involved, as detailed in the guide for candidates.) I want to stress this is a highly attractive position in terms of academic surroundings (research only campus, nearby Paris=Saclay and Orsay campuses), of location (Paris in the fields), and of status since permanent really means permanent!

the Hainish novels [book review]

 

When Ursula le Guin passed away earlier this year, I realised I had not read anything for her except for the Earthsea series. I thus ordered the two volume collection of the Hainish novels and short stories beautifully published by The Library of America. This boxed set has been at my bedside for the past six months and I completed reading the first volume while on Vancouver Island. The short novels (Rocannon’s World, Planet of Exile, City of Illusions) and both novels (The Left Hand of Darkness and The Dispossessed) are not part of a coherent cycle but relate to the same Universe, run by the mysterious Hains. Ursula le Guin herself describes the collection as a forest rather than a tree. There is nonetheless a strong common theme of displacement and of confrontation of one character with another culture, this character being often turned into the representative of his native culture. While the stories involve faster-than-light interstellar travel and mind reading and genetic engineering, their major thread is more of sociology or anthropology fiction than of science fiction. I enjoyed all these novels, both for their underlying common thread and for the massive diversity in the stories reported in the novels. If I had to pick only one, it would be The Dispossessed, as it merges a deeply realistic description of an anarchy run planet with the moving story of a top physicist faced with the individual doubts of pursuing research and the societal constraints imposed by a harsh arid planet and the pressure of the entire society. Albeit anarchist in principle, it still produces power structures and pressures, while being nationalistic at the planetary level by refusing any entry from another planet. In particular, I found most interesting the realisation by a group of friends that the society was no longer revolutionary and mostly replicating traditions and patterns. The reflections about scientific creativity and bareness in this novel as well as the power structures within academia are also most meaningful and should appeal to most researchers (and beyond!). Before the end of the Canadian trip, I was further able to read The Word for World is Forest in the second volume,  which is about the threat of destruction for a planet and its native humanoids, by Terrans seeking wood as the new gold. This theme has been reproduced in the subsequent sci’ fi’ literature, as in Orson Scott Card’s Speaker for the Dead, but the short novel remains striking (and in line with the permanent theme in Le Guin’s books of conflicting cultures and the difficulty to apprehend the fullness of the other culture(s)… Le Guin notes in the introduction to the second volume of the box that strong similarities have been pointed out about “a high-budget, highly successful film [which] resembles the book in so mamny ways that people have often assumed that I had some part in making it.  Since the film completely reverses the book’s moral premise, presenting the central and unsolved problem of the book, mass violence, as a solution, I’m glad I have nothing at all to do with it”. The film is Avatar, James Cameron’s 2009 blockbuster.

troubling trends in machine learning

This morning, in Coventry, while having an n-th cup of tea after a very early morning run (light comes early at this time of the year!), I spotted an intriguing title in the arXivals of the day, by Zachary Lipton and Jacob Steinhard. Addressing the academic shortcomings of machine learning papers. While I first thought little of the attempt to address poor scholarship in the machine learning literature, I read it with growing interest and, although I am pessimistic at the chances of inverting the trend, considering the relentless pace and massive production of the community, I consider the exercise worth conducting, if only to launch a debate on the excesses found in the literature.

“…desirable characteristics:  (i) provide intuition to aid the reader’s understanding, but clearly distinguish it from stronger conclusions supported by evidence; (ii) describe empirical investigations that consider and rule out alternative hypotheses; (iii) make clear the relationship between theoretical analysis and intuitive or empirical claims; and (iv) use language to empower the reader, choosing terminology to avoid misleading or unproven connotations, collisions with other definitions, or conflation with other related but distinct concepts”

The points made by the authors are (p.1)

1. Failure to distinguish between explanation and speculation
2. Failure to identify the sources of empirical gains
3. Mathiness
4. Misuse of language

Again, I had misgiving about point 3., but this is not an anti-maths argument, rather about the recourse to vaguely connected or oversold mathematical results as a way to support a method.

Most interestingly (and living dangerously!), the authors select specific papers to illustrate their point, picking from well-established authors and from their own papers, rather than from junior authors. And also include counter-examples of papers going the(ir) right way. Among the recommendations for emerging from the morass of poor scholarship papers, they suggest favouring critical writing and retrospective surveys (provided authors can be found for these!). And mention open reviews before I can mention these myself. One would think that published anonymous reviews are a step in the right direction, I would actually say that this should be the norm (plus or minus anonymity) for all journals or successors of journals (PCis coming strongly to mind). But requiring more work from the referees implies rewards for said referees, as done in some biology and hydrology journals I refereed for (and PCIs of course).

new kids on the block

This summer, for the first time, I took three Dauphine undergraduate students into research projects thinking they had had enough R training (with me!) and several stats classes to undertake such projects. In all cases, the concept was pre-defined and “all they had to do” was running a massive flow of simulations in R (or whatever language suited them best!) to check whether or not the idea was sound. Unfortunately, for two projects, by the end of the summer, we had not made any progress in any of the directions I wanted to explore… Despite a fairly regular round of meetings and emails with those students. In one case the student had not even managed to reproduce the (fairly innocuous) method I wanted to improve upon. In the other case, despite programming inputs from me, the outcome was impossible to trust.  A mostly failed experiment which makes me wonder why it went that way. Granted that those students had no earlier training in research, either in exploiting the literature or in pushing experiments towards logical extensions. But I gave them entries, discussed with them those possible new pathways, and kept updating schedules and work-charts. And the students were volunteers with no other incentive than discovering research (I even had two more candidates in the queue).  So it may be (based on this sample of 3!) that our local training system is missing in this respect. Somewhat failing to promote critical thinking and innovation by imposing too long presence hours and by evaluating the students only through standard formalised tests. I do wonder, as I regularly see [abroad] undergraduate internships and seminars advertised in the stats journals. Or even conferences.