PhD projects in our lab are available starting August 2018. Candidates should have a B.Sc. or M.Sc. in bioinformatics, computer science, or statistics, and be enthusiastic about science! Possible projects include:
- Machine learning approaches to predict cell fate from genomics data
- Single-cell transcriptomics of organoid disease models
- Modeling of alternative splicing using single cell ultra-long read RNA-Seq data
We are working closely with wet labs and the next genreation sequencing platform to generate large scale data. If you are interested in a PhD in Computational Biology, please contact Jonathan Göke by email (gokej at gis.a-star.edu.sg).
Computational Biology PhD Programme @GIS
The Genome Institute of Singapore (GIS) is the national flagship program for genomic sciences in Singapore. The department of Computational and Systems Biology (CSB) forms an integral part of GIS as data analysis hub and center of excellent computational research. CSB houses 9 dedicated computational research groups that bring together a rich expertise in computer science, statistics, and bioinformatics. The computational teams are supported by state-of-the-art sequencing facilities and high perfomance computing infrastructure that enables cutting-edge genomics research. PhD Students have the opportunity to directly interact with experimental and clinical research labs at GIS to facilitate truly inter-disciplinary and translational research projects. PhD students will be enrolled at NTU and NUS, consistently ranked among the best Universities in the world. The Computational Biology PhD program at the GIS offers a world-class learning environment and excellent career prospects both for academia and industry.
Singapore is a city-state with one of the highest standards of living in the world seeking to become an international hub for the biomedical sciences. Singapore is a vibrant, tropical city, with rich Asian heritage and modern style of living, an ideal gateway to explore Asia, providing a unique experience and an excellent quality of life.