Position: PhD Studentship
Research Area: Bioinformatics
Full/Part Time: Full Time
Investigator: Goh, Wilson Wen Bin
Date Posted: 29 June 2015
Description: The School of Pharmaceutical Science and Technology (SPST; Dean: Jay Siegel, PhD) at Tianjin University (TU), is seeking two PhD students to contribute to its bioinformatics initiatives within the Goh Research Group.
Our interest areas lies in 1/ the development of novel network-based algorithms for resolving consistency and coverage issues in proteomics data, 2/ specific application of bespoke algorithms for identifying potential biomarker or therapeutic targets in clinical research and 3/ leveraging our insights in proteomics as a means of pursuing panomic (genomics and transcriptomics) research. Disease paradigms we currently cover include breast, kidney and prostate cancer, neurological degenerative disease, as well as cardiovascular disorders.
The successful candidate will be expected to contribute productively towards the research and education goals within the SPST. In time, he/she can expect to become part of a close-knit international team with leading collaborators in Harvard (Cardiology), ETH Zurich (Proteomics) and the National University of Singapore (Bio-informatics/Statistics, Neurobiology).
Application: Please send your CV, an outline of your research interests, and names, phone numbers and email addresses of two referees to Dr. Wilson Goh (WILSON.GOH@TJU.EDU.CN).
Requirements: The candidate should have a background in any quantitative discipline (e.g. Computing, Bioinformatics, Biostatistics), an excellent command of spoken/written English and/or be highly independent and goal-driven. He/she should also have:
Good knowledge of statistics and mathematics
Proficiency in any one (or more) of the following scripting languages (PERL, Python, R, UNIX, Matlab, Java, C++)
Basic knowledge in biochemistry, molecular biology, network biology and mass spectrometry
Candidates with additional experience in gene expression analysis (microarray, NGS) will be considered more favorably.
