Research Fellow (CCB/OJ)

Job Description

We are looking for a motivated Research Fellow with expertise and background in machine learning, single-cell transcriptomics and drug perturbation databases e.g. CMAP, LINCS. This role will involve the development of new computational tools to prioritise drugs to reverse dysregulated pathways in different cancers and neurodegenerative diseases.

The successful candidate will be hired by Dr. John Ouyang and will be based within the Centre for Computational Biology (CCB), Duke-NUS. The selected candidate will apply cutting-edge machine/ deep learning approaches to develop new computational tools to predict how single cells respond to genetic / drug perturbations. 

The selected candidate will perform a variety of research activities under the supervision of the Principal Investigator, including but not limited to the following:

• Independently develop new computational tools through the application of machine learning / deep learning on single-cell and spatial transcriptomics data.
• Independently carry out computational and bioinformatics analysis for single-cell and spatial transcriptomics as well as next generation sequencing studies.
• Curate existing single-cell transcriptomics, gene pathway / network databases and drug perturbation databases as training data for new computational tools.
• Conceptualise new ideas and develop plans for computational method development through the application of machine learning onto single-cell data.
• Design and plan sequencing experiments to ensure proper downstream analysis.
• Write and review research papers, present research outcomes and develop connections with local and international researchers for collaboration work.
• Contribute to project management and provide guidance to junior researchers as well as undergraduate and graduate students.
• Perform other related duties incidental to the work described herein.

Job Requirements

• PhD in Bioinformatics/Computational Biology or a related scientific area with demonstrated bioinformatics expertise and experience.
• Experience with developing new computational tools written in R or Python.
• Experience with applying machine learning and statistical modelling packages.
• Prior knowledge with drug perturbation databases e.g. CMAP, LINCS is preferred but not necessary.
• Proven track record in the form of high impact publications. 
• A team player who is able to prioritise, multi-task and work collaboratively in a diverse workforce.

We regret that only shortlisted candidates will be notified. 

More Information

Location: Outram Campus

Organization: Duke-NUS Medical School

Department : Office of Research

Employee Referral Eligible: No

Job requisition ID : 21258