Key Role:

Seeking exceptionally talented bioinformaticians with a strong biostatistics background to join our bioinformatics team. The position will focus on analysis, application and processing of whole genome sequencing data generated. The successful candidate will work closely with our bioinformatics and science teams to support the exploratory analysis and reporting process. The ideal candidate should be a motivated team player with strong understanding of omics data, as well as experience in computational biology for building effective algorithms and tools necessary to support the clinical projects.

Responsibilities:

• Perform cutting edge biomarker identification from the data generated.
• Formulate hypothesis to perform analysis on whole genome sequencing study design, data processing, storage and analysis by building pipelines and databases for result retrieval and visualization.
• Develop novel methods and tools for analysis in the framework of our in-house data analysis platform.
• Integrate tools in pipelines and workflows and optimize their interoperability, efficiency, usability and portability.
• Able to perform data mining by retrieving public databases for pathway, network and disease associations and collate with proprietary data.
• Able to interpret and summarize the results into report, manuscripts and/or patents.
• Able to communicate and interact the bioinformatics results with the wet lab scientists.
• Support researchers in interdisciplinary project teams in various research areas.
• Other duties as assigned.

Requirements:

• Masters (MSc)/Doctorate (PhD) level individual with experience in computational biology, bioinformatics, statistics, and/or biological science.
• Equivalent research/industrial experience.
• Strong experience in at least one of these scripting languages: R, Python and/or Perl, knowledge with other object-oriented programming such as Python, C++ or Java is preferable.
• Experience with R and Bioconductor packages in analysis of biological data is an added advantage.
• Experience with machine learning algorithms is an added advantage.
• Prior knowledge of omics and molecular biology is an added advantage but is not necessary.
• Strong ability to work on multiple projects simultaneously and manage work with minimum supervision.
• Critical independent thinking, excellent prioritization of tasks, good team player, problem solving attitude, as well as excellent communications and presentation skills are favourable.