staying with R, jobs in R
Like Berton Gunter said, jobs are usually classified by subject than softwares used. It is difficult to change the mindset of people in a workplace that worships software A and condemns software B. Try learning enough of A to know its weakness/strengths and demonstrate some examples where B can do the job much better than A. Warning : This can be a slow and sometimes a pointless one. What you should be looking for instead is for a flexible and understanding employer that will allow you to experiment with other softwares. You could enquire about this before you apply for a given job. My biased opinion is that academic line gives you this flexibility. If you are interested in academia in UK, check out www.jobs.ac.uk. As for bio/pharamaceutical-related jobs, especially those dealing with *omics technology, knowledge of R and BioConductor can be a real advantage. Some of these are advertised on the BioConductor mail list. Regards, Adai
On Mon, 2005-08-29 at 11:04 -0500, Weiwei Shi wrote:
Hi, there: Could I ask another question, which is a little bit off-topic; but I tried hard and did not get good enough info... so please help I am very interested in seeing where to find those bio/pharmaceutical-related industries, using R and data mining as approaches? thank you very much! weiwei On 8/29/05, Berton Gunter <gunter.berton at gene.com> wrote:
Avneet: Not to throw a wet blanket on your enthusiam for R (which I share) but ... -- Bert Gunter Genentech Non-Clinical Statistics South San Francisco, CA "The business of the statistician is to catalyze the scientific learning process." - George E. P. Box Your better off finding a
job you like at a company you like and then convincing them that R is better (not to mention the R skill set you are bringing to the table). Good luck to you. Roger
Fine advice, but a tad unrealistic. The reality (according to Bert): 1. Most jobs for statisticians are in the pharmaceutical/medical industry (which includes academic research centers) in clinical trials. Data: See job ads in Amstat News. 2. For better or worse, in this arena SAS is the standard. You will **not** -- repeat, NOT -- convince industrial employers who have thousands of lines of legacy infrastructure code and legions of SAS programmers to change. You may well make some inroads in academic research venues. In both, you will generally be free to use whatever software you like for your own work, but the final code submitted for FDA approval will almost certainly necessarily be SAS. Rail all you like, but those are the realities. 3. Another significant amployer of statisticians these days is the "finance" industry (credit scoring and the like). Data: See Amstat News ads again. There S-Plus is already widely used, so you should have no difficulty using R and even getting others to adopt it. I think outside these arenas -- for example, in industrial research and engineering centers or in pre/non-clinical pharmaceutical work, you'll again be free to use what you like. But there are relatively few jobs there, so that despite Roger's noble advice (with which I again agree), first you gotta eat and pay the mortgage. And I also say: good luck. -- Bert -- Bert Gunter Genentech Non-Clinical Statistics South San Francisco, CA "The business of the statistician is to catalyze the scientific learning process." - George E. P. Box
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