[R] staying with R, jobs in R

[Adaikalavan Ramasamy]

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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> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
> > 
> 
>