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The Lee Kong Chian School of Medicine (LKCMedicine) trains doctors who put patients at the centre of their exemplary care. The School, which offers both undergraduate and graduate programmes, is named after local philanthropist Tan Sri Dato Lee Kong Chian. Established in 2010 by Nanyang Technological University, Singapore, in partnership with Imperial College London, LKCMedicine aims to be a model for innovative medical education and a centre for transformative research. The School's primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised for the quality of its medical expertise, facilities and teaching. The School is transitioning to an NTU medical school ahead of the 2028 successful conclusion of the NTU-Imperial partnership to set up a Joint Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in healthcare, with an expanded scope in the medical humanities. Graduates from the five-year undergraduate medical degree programme will have a strong understanding of the scientific basis of medicine, with an emphasis on technology, data science and the humanities.
We are seeking a motivated Research Fellow / Senior Research Fellow to join our research team to support research activities, which focus on understanding the roles of ageing, inflammation and microbial influences on pancreatic health. The candidate will play an important role in advancing research activities through the coordination of experimental studies, animal models, organisation and management of research data, and integration of results across multiple study components. The successful candidate will contribute to data analysis, interpretation of findings, and preparation of reports, presentations, and scientific publications. In addition, the candidate will work closely with collaborating researchers and stakeholders to ensure the smooth implementation of study activities and timely achievement of project milestones.
Key Responsibilities:
Carry out mouse handling and experimental procedures in accordance with approved ethical and institutional guidelines, including animal monitoring, metabolic assessments, tissue harvesting and biological sample collection and processing
Perform and support metabolomic and transcriptomic sequencing analyses including sample preparation, processing, quality control for downstream sequencing and data analysis
Assist in the integration, analysis and interpretation of multi-omics datasets to support research objectives
Collaborate closely with cross-disciplinary teams, including internal team members and external collaborators to support project implementation and data driven research objectives
Contribute to grant writing, publications in peer-reviewed journals and present research findings at conferences, seminars and meetings
Support the timely achievement of research milestones and contribute to the overall advancement of ageing and disease-related research initiatives
Required educational qualification, experience, skills and competencies:
PhD degree in Biomedical Science, Molecular Biology or related field
At least 3 years of relevant hands-on experience in mouse handling and laboratory animal work RCULA certification will be advantage
Strong laboratory research skills with the ability to design, conduct and troubleshoot independently
Strong analytical, critical thinking and problem-solving skills with the ability to interpret complex biological datasets
Demonstrated ability to work independently as well as collaboratively within multidisciplinary and cross-institutional research teams
Good project management and organisational skills, with the ability to manage multiple priorities and meet project timelines
MBBS
Job ID: 149273785
Skills:
biological databases , Bash, Linux, Python, Bioinformatics pipelines, Data Analysis, Statistical analysis methods, High-performance computing, Bioinformatics software and tools, Multi-omics integration, R, Reproducible research practices, Omics analysis platforms, Data integration approaches, Bioinformatics
Skills:
latent class analysis , causal inference , Machine Learning, Scala, Pyspark, Sql, Deep Learning, Spark, Statistical Modelling, Python, omics analytics, LOINC, Cpt, snomed, RxNorm, NDC, R, survival modelling, OMOP Common Data Model, ICD10-AM
Skills:
Machine Learning, Statistical Techniques, Data Analysis
Skills:
Version Control, Data Collection And Analysis, 3D model management, water channel experiments, environmental field measurements
Skills:
Statistical Analysis, Epidemiological principles, Study Design, Quantitative data collection techniques, grant writing
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