Lee Kong Chian School of Medicine invites applications for:

Bioinformatic Research Associate in the Laboratory of Asst. Prof. Sarah Langley

The laboratory of Asst. Prof. Sarah Langley at the Lee Kong Chian School of Medicine is currently recruiting a Bioinformatic Research Associate to work in the area of omics integration and analysis.

We are a newly formed computational biology research group focused on understanding disease mechanisms through the analysis of, and method development for, large-scale omics data. The laboratory is based at the Lee Kong Chian School of Medicine (LKCMedicine), a joint medical school between Imperial College London and Nanyang Technological University (NTU).

We are looking for a highly motivated bioinformatician with an interest in human disease and omics integration/analysis.

Responsibilities:

Provide leadership and expertise in conducting complex research activities, including but not limited to planning, organizing, conducting, and communicating research studies within the overall scope of research projects at LKCMedicine.

• Utilize and/or developing computational tools, including but not limited to, those written in R/Python/Java
• Develop and use next generation sequencing pipelines for projects within the group
• Maintain up-to-date knowledge of bioinformatics tools and related research efforts
• Provide guidance and support to researchers, undergraduate and graduate students
• Perform other related duties incidental to the work described herein

Skills and qualifications:

• Masters or equivalent research experience in a related scientific area (eg Bioinformatics, Computational Biology, Life Sciences, Computer Sciences, Statistics)
• Experience with R/Python/Java or similar languages and with Unix based platforms
• Knowledge of next generations sequencing (genomics, bulk and/or single cell transcriptomics), mass spectrometry proteomics, neuroscience, statistics, bioinformatics or high dimensional data analysis
• Strong project management skills
• Ability to work harmoniously with a diverse workforce
• Expertise in publication-grade data visualization is highly desirable

Application Procedure:

If you are interested to pursue a career with the School, please apply with your cover letter, CV and names/ contact details of two references at your earliest convenience.

Only shortlisted candidates will be notified.