How Best Identify Bioinformatics Candidate

Question

[Soon Paik]

I am currently looking for a bioinformatics specialist for the lab which serves as the translational research lab for a large multi-center clinical group funded by NCI/NIH. We have been mainly working with gene expression arrays but now we are moving toward sequencing. The bioinformatics specialist has to work with our biostatistic center since they have all clinical data that needs to be linked to genomics data. We expect the person to have expertise in prognostic or predictive model building, as well as having a solid biostatistics skills such as survival analyses with censored data from clinical trials.

What would be the best way to identify such candidate?

Thanks for your help!

Answer 1

[Obi Griffith]

Bioinformatics and Biostatistics specialists are in quite high demand, especially those with solid next-gen sequence analysis experience. Depending on how desirable your city/lab are you may have to cast a very wide net. See this previous post for a great list of suggestions of where to put up job postings. If you can afford it, there are also some recruiters who specialize in this. For example, try searching LinkedIn for "bioinformatics recruiter". I am personally aware of two (FPC Cambridge and Aron/West) which have a bioinformatics track record. Be prepared to offer competitive salary and benefits if you want someone good. If the position is not academic/tenure track and you want someone long-term and reliable you might also consider avoiding the usual prejudice against those without a PhD. There are some really excellent bioinformatics specialists with a Masters who have been working in the field for a long time before getting a PhD became almost mandatory.

Answer 2

[Larry_Parnell]

According to a recent article in Forbes (27 Apr 2011), there are really only three questions to pose to a candidate interviewing for a job:

1. Can you do the job?
2. Will you love the job?
3. Can we tolerate working with you?

Q1 asks about strengths. Q2 queries motivation. Q3 asks about fit.

[DG]

A good bioinformatician will have a fairly flexible toolset, and above all, be willing and able to learn new techniques. And for lots of different analysis (such as survival analysis) there may already be many different implementations available. So rather than having a whole checklist of areas where they must have expertise, look for someone well rounded who can think on their feet. Obviously someone who fits that bill that also already has lots of experience in key areas will outrank someone who doesn't.

Answer 3

[Gjain]

Hi Soon,

Now a days there are several avenues available to identify the best candidate for the job.

You could first research and identify professors/professionals/labs/institutes who are doing NGS analysis, cluster computing and traditional micro array analysis and look for the personnels who have interacted with them. This will help you isolate the pool of potential candidates.

Next step would be to go through some social media networking tools like LinkedIn, Phdcomics etc to get a description of their experiences.

I hope this helps.

Answer 4

[Andrew Su]

See also this previous question

I'm going to double down and repeat my answer here:

We've just recently started asking candidates to do a code review with the existing team/group members. It can be on any piece of code from their past -- I tell them to choose something that they're passionate about, and that demonstrates the skills that are relevant to our job posting. It works great. Covers everything from coding style to communication skills to documentation to programming ability. I highly recommend this approach...

I've been using that method for over two years now and it hasn't failed me yet. It does mean you end up being rather selective -- you find that some people who look great on paper aren't so good in practice...