Dr David Clifford is a Research Scientist working on bioinformatics for agribusiness
Dr David Clifford: bringing a statistical perspective to bioinformatics
Dr David Clifford is a researcher who uses his skills in statistics to make sense of large and complex biological datasets.
2 July 2010 | Updated 14 October 2011
Dr David Clifford's research has taken a new direction since he joined CSIRO, from spatial statistics, in which he completed his doctoral studies, to statistical bioinformatics.
Bioinformatics is about using mathematics, statistics and information technology to extract useful information from large and complex biological datasets.
Dr Clifford's current projects include:
developing biosensors with colleagues in the Food Futures Flagship by analysing the data collected from the electronic nose
detection of human growth hormone in athletes, and analysis of its effect on an athlete's body and performance.
Dr Clifford joined CSIRO in 2004 as a Postdoctoral Fellow and has been a Research Scientist with CSIRO Mathematics, Informatics and Statistics Division since 2006.
Dr Clifford is currently working on the detection of human growth hormone in athletes.
Dr Clifford is from Cork, Ireland and completed his doctoral studies at the University of Chicago, United States of America (USA).
Since joining CSIRO, Dr Clifford has collaborated with researchers across CSIRO, from The University of Sydney, New South Wales, Australia and the University of Chicago.
Dr Clifford has been awarded a:
Bachelor of Science in Mathematics and Statistics from the National University of Ireland, Ireland in 1999
Master of Science in Statistics from the National University of Ireland, Ireland in 2000
Doctor of Philosophy in Statistics from the University of Chicago, USA in 2004.
Dr Clifford's achievements include being awarded:
an International Science Linkages grant for 2010-2011 from the Australian Academy of Science
the 2003 Consulting Award from the University of Chicago, USA
a Fulbright Scholarship in 2000.
Read more about CSIRO's work in Smart statistics for bioinformatics.