Postdoctoral/Research Fellow (Bioinformatic and Computational Biology)

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/PostdoctoralResearch-Fellow-%28Bioinformatic-and-Computational-Biology%29/34941-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

We are looking for Statisticians, Bioinformaticians, or Computational Biologist Snr Postdoc/Postdoc to join the Patani lab at NUS. The Patani lab has played a pioneering role in understanding the molecular and cellular mechanisms underpinning motor neuron disease (ALS). The lab uses a variety of patient-derived iPSC lines to investigate disease-related events at the molecular level across different relevant cell types, including motor neurons, astrocytes, and microglia. The lab is seeking creative and driven Statisticians, Bioinformaticians, or Computational Biologist Snr Postdoc/Postdoc with experience investigating disease-related events at the molecular level across different relevant cell types, including motor neurons, astrocytes, and microglia to join the group. The individual will report directly to Prof. Patani.

Job Description & Key Responsibilities

The post holder will join a dedicated team researching Motor Neuron Disease (ALS) using human induced pluripotent stem cells. They will investigate motor neuron degeneration, focusing on genomic instability and RNA metabolism using stem cell models. The role involves advanced molecular methods and sequencing in collaboration with the Boulton lab at the Francis Crick Institute. This is an opportunity to contribute to impactful research within a diverse scientific community.

Research Fellow: Collaborate with Senior Research Fellows and scientists to lead computational projects, develop quantitative and analytical strategies, and guide experimental validation. The individual will gain scientific and analytical independence over time.

Key Responsibilities

• Design and manage a research programme to achieve agreed objectives.

• Collaborate effectively with experimental and data scientists in the group to support project progress.

• Oversee the setup and execution of planned experiments, ensuring proper supervision and assistance.

• Ensure that results are recorded, analysed, and documented promptly.

• Prepare and present research findings to colleagues.

• Submit papers to relevant journals and participate in presenting findings at appropriate conferences.

• Train and supervise students and staff members on various techniques and the design of experimental protocols.

Teaching, Research, and Development

• Provide teaching on topics related to the post holder’s work as requested by the line manager.

• Contribute to the department’s multidisciplinary research projects in alignment with the strategy.

• Prepare and analyse data for publications to disseminate research and for presentations at international conferences, internal meetings at NUS, and meetings with external collaborators.

General Duties

• Maintain accurate, complete, and current records with strict confidentiality

• Participate in Departmental and Institutional meetings.

• Uphold professional standards in all research activities.

• Work resource-efficiently and support NUS Sustainability goals.

• Follow all Department, Institute, and NUS policies and regulations.

The above description is not exhaustive, and the post holder will be required to undertake any other duties as may reasonably be requested within the scope, spirit, and purpose of the post.

Qualifications

• Hold a PhD in bioinformatics, computational biology, statistics, biostatistics, applied mathematics, quantitative biology, or a closely related discipline.
• Demonstrate a strong research track record appropriate to career stage, including first- or co-first author publications demonstrating substantial intellectual or quantitative contributions.
• Demonstrate the ability to independently design and conduct rigorous computational or statistical investigations.
• Demonstrate experience analysing complex biological datasets and taking projects from raw data through statistical analysis, biological interpretation and publication.
• Have strong foundations in statistics and quantitative reasoning, including an understanding of experimental design, confounding, multiple testing, uncertainty and appropriate model validation.
• Demonstrate experience developing, adapting or critically evaluating computational/statistical approaches beyond relying exclusively on established analysis pipelines.
• Demonstrate the ability to work closely with experimental scientists to translate biological questions into analytical strategies and computational findings into experimentally testable hypotheses.