Job Description

The National University of Singapore invites applications for a Research Assistant (Bioinformatics Specialist) for the project “Uncovering and developing Insertion Sequences for large gene editing of 50 bp–1 kb in mammalian cells” in the Department of Biochemistry, Yong Loo Lin School of Medicine. The Department undertakes excellence in research and scholarship through intimate support of our faculty and staff in the NUS Medicine Translational Research Programmes (TRPs). Our scientific strengths and leadership are evidenced by Biochemistry being the academic home of 4 TRP Directors, and by stellar research scholarship in cancer, cardiovascular disease, digital medicine, healthy longevity, human potential, infectious disease, immunology, precision medicine and synthetic biology. Appointments will be made on a 1-year contract basis in the first instance, with the possibility of extension.

Purpose of the post

We are seeking a motivated Bioinformatics Specialist to support computational genomics and genome engineering research. The successful candidate will develop bioinformatics pipelines to analyse large-scale genomic and metagenomic datasets, identify and characterise novel insertion sequences, and support the discovery of genetic elements suitable for large DNA cargo insertion in mammalian cells.

The role will also involve applying machine learning and AI approaches to analyse genomic data, predict and optimise genetic elements, and extract biological insights from genomic datasets and foundation models. The successful candidate will work closely with computational and experimental researchers to translate bioinformatics findings into candidates for experimental validation.

Main duties and responsibilities

The Research Assistant will:

1. Develop and automate bioinformatics pipelines for the analysis and mining of genomic and metagenomic datasets.
2. Identify, characterise and analyse novel insertion sequences and transposable elements from microbial and other genomic datasets.
3. Perform sequence analysis, comparative genomics, genome annotation and functional analysis to identify candidate genetic elements for genome engineering applications.
4. Develop computational and machine learning approaches to predict and optimise genetic elements for large DNA insertion in mammalian cells.
5. Apply AI and explainable machine learning approaches to extract biologically meaningful insights from genomic datasets and genomic foundation models.
6. Develop reproducible and scalable computational workflows and maintain well-documented code, pipelines and analysis results.
7. Analyse and integrate large-scale genomic datasets to generate hypotheses and identify promising candidates for experimental validation.
8. Collaborate with experimental biologists and computational researchers to support the design, interpretation and validation of research findings.
9. Assist in the preparation of research reports, presentations, manuscripts and other scientific outputs.
10. Perform other duties as assigned by the PI.

Qualifications

The applicant should have:

1. A Bachelor’s or Master’s degree in Bioinformatics, Computational Biology, Computer Science, Data Science, Biology, Genomics or a related field;
2. Strong programming skills in Python, R or similar programming languages;
3. Experience or strong interest in bioinformatics, genomics, metagenomics or computational biology;
4. Familiarity with genomic sequence analysis, genome annotation, sequence alignment and comparative genomics;
5. Experience in developing bioinformatics pipelines and/or working in Linux/Unix environments would be advantageous;
6. Knowledge or experience in machine learning, artificial intelligence or data science would be advantageous;
7. Strong analytical and problem-solving skills, with the ability to work independently and develop computational solutions to biological research questions;
8. Good verbal and written communication skills, with the ability to clearly document computational analyses and research findings; and
9. Ability to work effectively in a multidisciplinary research environment.

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be made to Ms. Anna Gan (anna.gan@nus.edu.sg).

Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations (if any) and full contacts of three (3) referees) to this job portal.

We regret that only shortlisted candidates will be notified.