Scientist, Laboratory of Computational Transcriptomics (GIS)

Agency for Science, Technology and Research (A*STAR); Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

The Genome Institute of Singapore is seeking a postdoctoral fellow to develop computational methods for long read RNA-Seq data. This role involves analyzing transcript expression related to neurodegenerative diseases, collaborating with a skilled team, and contributing to significant research projects in a vibrant city-state known for its high living standards.

Benefits

Competitive salary

Complete benefits package

Qualifications

• PhD in relevant field required.
• Good programming skills and interest in methods development.
• Experience in algorithms development, RNA modifications, and statistics.

Responsibilities

• Develop computational methods and pipelines for long read RNA-Seq data.
• Analyze transcript expression and alternative transcription start sites.
• Collaborate with experimental and clinical teams.

Skills

Programming skills

Methods development

Transcriptome analysis

Machine learning

Education

PhD in Bioinformatics, Computer Science, Statistics, Genomics, or a related discipline

Job description

The lab of Computational Transcriptomics at the Genome Institute of Singapore (led by Dr Jonathan Göke) is offering a position for a postdoctoral fellow to work on long read single cell and spatial RNA-Seq data. The position involves development of computational methods and pipelines for long read RNA-Seq data, and the analysis of transcript expression, alternative promoters and alternative transcription start sites from single cell and spatial long read RNA-Seq. The project aims to study the transcriptome of neurodegenerative diseases using mouse models and human brain organoids. The position will be in close collaboration with experimental and clinical collaborators and will provide resources for large-scale data generation and full access to the latest long read sequencing technologies.

The candidate will join an experienced team with expertise in methods development for long read RNA-Seq data (e.g. bambu, Nature Methods (2023), xPore, Nature Biotechnology (2021), m6Anet, Nature Methods (2022)), large scale transcriptomics data generation (e.g. the SG-NEx project) and the analysis of large-scale transcriptomics data (e.g. Demircioglu et al, Cell (2019)). More information about the lab can be found online: https://www.jglab.org/ and www.github.com/goekelab

Requirements:

· PhD in Bioinformatics, Computer Science, Statistics, Genomics, or a related discipline

· Good programming skills and strong interest in methods development

· Experience in one or more of the following areas: algorithms development, transcriptome analysis, RNA modifications, statistics, machine learning, long read RNA-Sequencing, direct RNA-Sequencing

· Publication record with a first author publication (pre-prints are accepted)

· Excellent communication skills

We are searching for promising candidates who are great team players and actively seek opportunities to learn new skills. If you are unsure about your eligibility, please feel free to reach out via email.

Benefits

The Genome Institute of Singapore offers a competitive salary and a complete benefits package that ensures a very high living standard in one of the most modern cities in the world.

About Singapore and the Genome Institute of Singapore

Singapore is a city-state with one of the highest standards of living in the world and 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.

The Genome Institute of Singapore (A*STAR) is the national flagship program for genomic science in Singapore. You can find out more online: http://www.gis.a-star.edu.sg/

Contact and further information: For inquiries or to apply, please email your CV and a short introduction about yourself, your past research experience and your future research interests to Jonathan Göke ([e-mail])