Analytics | Big Data
NGS data analysis | MS | PhD | gene expression | bioinformatics
We are seeking a motivated Computational Biology Scientist with expertise in NGS data analytics including single-cell analyses and/or methods development to join Proteona’s research team in Singapore. Proteona Pte Ltd is a young, venture backed company and you will have the opportunity to play multiple roles, learning both the science and the business of cutting edge biotechnology. Our work is dynamic and you will need to be able to handle multiple tasks and switch between them as quickly as is necessary. Proteona is focussed on using single cell proteogenomic analysis to improve patient outcomes. To this end, experience in one or more of the following areas is highly desired:
- single-cell characterization (scRNA-Seq)
- gene expression analysis (RNA-Seq, eQTL, Pathway analysis)
- bioinformatics engineering (programming, analytical pipeline development, data visualization, high-performance computing)
- machine learning (decision theory, clustering, network analysis)
Your key tasks will be to collaborate with scientists both in the wet and dry lab to design studies, analyze and interpret scRNA-Seq data, develop and implement new analysis techniques and communicate results that will have critical impact on patient treatments. Proteona is based in Singapore, but we are open to remote working arrangements for the right candidate.
Work with other wet and dry lab scientists to analyze data. Develop new methods of analysis. Work hard to improve the quality of cancer treatment.
- PhD or exceptional MS with experience in computational biology, bioinformatics, machine learning or a related field
- A proven track record in the analysis, and interpretation of genomic and NGS data. Single cell RNA-Seq experience is a plus.
- Demonstrated ability to work closely with project teams and/or experimental collaborators to design studies and develop analyses to answer scientific questions
- Familiarity with relevant analytical approaches and underlying assumptions
- Detail-oriented and self-motivated approach to problem solving with excellent reasoning skills
- Strong organizational and time-management skills to prioritize needs and get things done
- The interest and the will to improve modern medicine