Research Fellow (Microbiology & Immunology) - Part-Time

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link: https://careers.nus.edu.sg/job/Research-Fellow-%28Microbiology-&-Immunology%29/22121-en_GB/?st=8D4EEF9B0E1A95200D1286536EB80500394C0095

We regret that only shortlisted candidates will be notified.

Job Description

The National University of Singapore invites applications for Research Assistant for “Singapore Integrated Network for Genomic and Epidemiological Tick-borne Pathogen Investigation and Connectivity” in the Department of Microbiology & Immunology, Yong Loo Lin School of Medicine. The Department of Microbiology and Immunology (https://medicine.nus.edu.sg/mbio/) at NUS is dedicated to advancing research, teaching, and training in infectious diseases, immunity, and host-pathogen interactions. It is well known for strengths in immunology, virology, bacteriology, parasitology, and molecular biotechnology, supported by strong core research facilities and graduate training opportunities. Appointments will be made on a 1-year contract basis in the first instance, with the possibility of extension.

Purpose of the post

The Research Fellow (RF) will work closely with the Principal Investigator (PI) and study team to ensure timely, high-quality delivery of a tick and tick-borne disease biosurveillance project in Singapore. The RF will support end-to-end study operations, including coordination with study sites, participant/sample workflows, data management, analysis, and reporting, while maintaining strong professional standards and accurate documentation.

Main duties and responsibilities

The RF will liaise with relevant personnel across study sites (e.g., clinics/hospitals and partner units) to support smooth recruitment and data/sample collection processes and will be accountable to the PI. The RF will be able to:

1. Oversee the general management of the project, including planning, coordination and day-to-day troubleshooting to ensure milestones are met;
2. Provide administrative and secretarial support to the project, such as organizing regular meetings to maintain regular communication with other members of the research team and collaborate with the study sites;
3. Undertake the day to day running of the project at the study site, e.g. collaborate with team members at the study sites, support recruitment, coordinate field/site activities, and support data and/or sample collection at sites and relevant settings;
4. Conduct literature searches, support maintenance of the study database, perform data entry and cleaning, and analyse data using appropriate software tools; as well as assist in preparing both progress and final reports of the project;
5. Apply bioinformatics and AI-enabled approaches to support genomics and proteomics-related analyses as required by the study (e.g. use relevant bioinformatics tools and machine learning/deep learning workflows to support interpretation and reporting);
6. Maintain the highest standard of professional conduct and record keeping in accordance with policies and procedures, including accurate documentation and data integrity.

Qualifications

The applicant should:

1. Have a first degree with good results or holds a PhD degree in Biotechnology, Microbiology, Biochemistry, Molecular Biology;
2. Have a background in infectious pathogens and infection-related research, with training/exposure in microbiology, immunology and/or clinical microbiology, and experience working with pathogen-focused research questions;
3. Be able to work independently and in a team, have an investigative nature and attention to detail, and be able to deliver reports and presentations to stakeholders;
4. Have knowledge of computer applications and research software for data handling, analysis and reporting (e.g. MS Office/PowerPoint, EndNote/Mendeley, GraphPad Prism) and be familiar with computational/bioinformatics tools and workflows (e.g. machine learning approaches and sequence-based tools such as BLAST);
5. Have experiences in relevant areas of research spanning wet-lab and computational work, such as microbiology/molecular biology methods (e.g. biofilms, RNA extraction, RT-qPCR, ELISA, mammalian cell culture) and computational/AI methods (e.g. virtual screening/docking, molecular dynamics simulations, and machine learning model development).

Remuneration will be commensurate with the candidate’s qualifications and experience. Informal enquiries are welcome and should be made to Dr Benoit Malleret at [email protected].

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 and full contacts of three (3) referees to the NUS Career Portal.

We regret that only shortlisted candidates will be notified.