Research Associate, Lee Kong Chian School of Medicine
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.
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
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.