A post-doctorate research associate position in bioinformatics is available in my lab (click on Apply button on the following links to submit the credentials rather than emailing me directly):
I am looking for an exceptionally-talented individual with a background in computational/statistical science. Ideally the person should have exposure to working on Linux-type servers (know how of bash/awk scripting) with knowledge of programming languages (e.g. C/C++, Python, Perl, R, HTML, Java etc). The job would require expert knowledge in processing, analysing and integrating omics datasets to be generated from the recent research grants on microbes (http://userweb.eng.gla.ac.uk/umer.ijaz/#research_Grants), managing my Orion cluster (http://userweb.eng.gla.ac.uk/umer.ijaz/#orion), developing workflows and scientific software (http://userweb.eng.gla.ac.uk/umer.ijaz/#bioinformatics) by focusing on methods development [keywords: machine learning, bayesian statistics, signal processing (time/frequency domain), ecological statistics etc].
Some recent contribution (last 3 years) to bioinformatics software include:
NMGS (Proceedings of the IEEE, 2017; http://dx.doi.org/10.1109/JPROC.2015.2428213)
RVLab (Biodiversity Data Journal, 2016; http://dx.doi.org/10.3897/BDJ.4.e8357)
CONCOCT (Nature Methods, 2014; http://dx.doi.org/10.1038/nmeth.3103)
The prospective candidate will become part of the vibrant Water & Environment Research Group (https://www.gla.ac.uk/schools/engineering/research/divisions/i&e/researchthemes/w&e/) where we are tackling some of the globally important environmental problems by harnessing the most up-to-date theoretical and experimental advances in science. In particular, we are focusing on molecular microbiology, theoretical evolutionary biology, flow cytometry and imaging technologies, microfluidics, novel chemical analysis and bioinformatics.
Please note that the position is available for 28 months in the first instance (there is a high likelihood of extension commensurate with experience/further grants going through) and will be co-advised by Professor William T. Sloan (https://www.gla.ac.uk/schools/engineering/staff/williamsloan/) on mathematical modelling.