On the attractiveness of research institutions

The job market for research tenured position is changing. First, as emphasized in a recent Nature issue, the number of graduating PhD is exploding. However the overall number of accepted papers in top-ranked conference is still desperately low. Hence, the vast majority of graduated PhD have a few minor publications and a h-index below 5. These young ambitious researchers are in the long tail of the scientists. Second, as illustrated by the closing of Intel Labs, the number of scientific jobs in private companies is dangerously decreasing. It seems that the future of research in private companies is about maintaining partnerships with universities and about outsourcing scientific studies to the right experts. In the meantime, the number of job openings in academic institutions is relatively stable. Third, academic institutions now hire scientists from all over the world. One of the consequences of the Shanghai ranking is that institutions do no longer focus on native candidates, and that many scientists look for jobs out of their native country.

Please forget the most prestigious universities and the best young scientists. Both know how to match each other. Let's rather observe the second league: the thousands of more or less famous ambitious institutions, which want to attract the best scientists, and the thousands of more or less unknown ambitious scientists who want to join the best institutions. We are in a typical assignment problem, where institutions and scientists of similar ranking should agree.

Many indicators have been proposed for the comparison of scientists. As well, many indicators or classification exist for ranking institutions for under-graduating students. But, I don't know how to measure the attractiveness of an academic institution for candidates to a tenure-track position.

Of course, three criteria prevail:

• the salary. The romantic vision of the scientist who does not care of money is wrong. Scientists are humans living in a capitalist world.
• the location. It includes weather, probability that the family members can enjoy (employment, schools, etc.), cultural life, and so on.
• the prestige of the institution. A scientist builds a career, her resume should maximize the number of famous entries and minimize unknown ones.

Now, some more specific criteria include:

• the number of free PhD students. Here, free means that the scientist does not have to produce any effort to have the guarantee that this number of PhD students will be under her advices in her lab.
• the volume of teaching. It should not be too high because teaching must have no impact at all on the paper productivity. But it should not be too low because teaching is also a way to meet future PhD students.
• the quality of students. Every scientist knows that bad students can be a significant waste of time, although great students can boost the productivity without much efforts.

I am quite suspicious about the importance of having top-class colleagues within the same area. Ambitious scientists have their own research area, and a majority of them have their own agenda, without regards to other scientists. This thought leads me to another criteria:

• the autonomy. From a scientific point of view, a researcher prefers to define her own research axis, and to write her own research proposals, without having to justify anything. From a more practical point of view, a researcher is likely to receive grants for her research, but this money goes first through her institution, which can constraint the expenses. Consequently, a scientist might be not free to buy her own equipment, not free to travel as she wishes, not free to set the salary of a post-doc, ... 

Is there any other criteria? Of course, every researcher can introduce her own weight on this criteria, depending on her personal priority.

It is now easy to analyze institutions. Typically, my current employer, Telecom Bretagne (member of Institut Telecom) :

Salary	7	Good salary when you join, low increasing though
Location	4	France is great, I do recommend Brest for a family with kids, but it is actually considered as a sub-attractive place in France
Prestige	3	I am afraid that recent branding operations have significantly affected the reputation of the institution, nobody knows Institut Telecom
Nb of free PhD students	4	No free PhD student at all, but it is not hard to obtain funding for one PhD student from the institution
Volume teaching	7	It is highly negotiable with your colleagues, you can be involved in research-oriented project management rather than formal time-wasted courses
Student quality	8	Very good engineering students, however very few are interested with research
Autonomy	8	You are definitely free to do what you want, you are almost free to manage your own budget (personal, travel, equipment)
Total	41/70

And Orange Labs, Issy-les-Moulineaux

Salary	8	Good salary when you join, good opportunities to increase
Location	9	Paris is one of the most attractive cities in the world
Prestige	5	France Telecom was a strong actor of the research, Orange is a well-known brand, but the research center is no longer a key academic player
Nb of free PhD students	2	No free PhD student at all, very hard to obtain it without significant efforts
Volume teaching	5	No teaching at all, but not difficult to find some courses in nearby universities
Student quality	4	No contact with students, but some students (not the best, though) might be interested with research internships
Autonomy	2	Not free at all. You have to justify your research axis, and, worse, you have to justify any expense, even for funded projects
Total	35/70

Now, we should create a website in order to gather ratings from several scientists, a kind of tripadvisor for scientific institutions.

inside the FP7 evaluation (last part): how to build funded proposals

Don't expect any miracle from this post, and don't expect anything for posts with similar titles: there is no unique recipe for winning proposal. However, I can sketch a few tips that I will at least try to apply to my own proposals:

• In the specific case of the FP7 STREP, every proposal is read by only three reviewers (no more no less) randomly picked among a set of very diverse reviewers, from experienced academics to young industrials (and vice versa) from various countries. Contrarily to the funding process of Google, there is no single reviewer target. Therefore, proposals should cover several "reading styles". Hopefully, there is no page limit, so don't hesitate to explain things several times in several ways.
• The Criteria 1 ("Scientific and Technical Quality") can kill a proposal, but it can hardly make a winner. Your objective is to not give any opportunity for reviewer to criticize, so don't waste your energy there, just do a clean job. Recall that STREP is not about new scientific breakthrough, it is about incremental but sure progresses beyond State-of-the-Art. No reviewer can argue against a series of incremental loosely-consistent progresses in several domains. A bad note in Criteria 1 is more often due to a faulty or unconvincing workplan. Don't try to produce super-clever ambitious workplan, but describe things (scientific ideas and, more important, processes) that have 100% chances to be implemented. Revise your workplan a lot because some reviewers harshly track inconsistencies.
• You have to differentiate, and the best place is Criteria 3 ("Exploitation and Dissemination"). The majority of proposals do not provide any market analysis, only claim standard dissemination plans, and describe very vague exploitation plans. The best proposals include real-world experimentations during the projects (which is actually appreciated), contain some partners that are actually involved in standardization processes, or have already identified some third-party companies to include in the proposal as external partners (or in a associated committee). The exploitation plan should be preferentially written at the beginning of the project, because it has a direct impact on the partners in the consortium, on the perimeter of the required scientific progresses and on the workplan (e.g. a real-world experimentation requires a specific work-package and a early prototype from technical work-packages). When the exploitation plan is strong, the whole project is fully consistent.

I know that the usual process is definitely not this one. We usually work a lot on the scientific breakthroughs, trying to copy-paste endless bibliographic works written by students, to incorporate old scientific friends and to make the whole stuff as consistent as possible. Then, we let every partner write its own work package, and we argue a lot about the number of men/months and fundings. Finally, we have a few hours to write some crappy paragraphs about the exploitation. And we have wasted at least one month because the resulting proposal is all but a winner...