Prof. Junwen John Wang’s lab (facdent.hku.hk/about/staff-profile.php?shortname=junwen) at The University of Hong Kong (HKU) is recruiting outstanding candidates for Research Assistant/PhD student in bioinformatics and precision dentistry/medicine. The lab currently focuses on two main areas: 1) integrative analysis of multi-dimensional OMICs data for gene regulatory network inference from bulk and single cell sequencing data, 2) function annotation of genetic variants, particularly these in the noncoding regulatory regions. The lab is also actively collaborating with biologists and clinicians on data analysis in ATAC-seq, RNA-seq and WGS/WES (Whole Genome/Exome Sequencing) data generated from HKU Faculty of Dentistry/Medicine and Mayo Clinic, the top hospital in the USA.
For PhD applicant: The lab is hosted in Faculty of Dentistry (facdent.hku.hk/) and can recruit PhD/MPhil students from both the faculty (facdent.hku.hk/learning/research-postgraduate-programmes.html) and the interdisciplinary Biomedical Engineering program (www.engineering.hku.hk/bmeengg/curriculum/bmerpg/). The candidates are welcome to apply for external fellowships, including the Hong Kong PhD Fellowship Scheme (gradsch.hku.hk/prospective_students/fees_scholarships_and_financial_support/hong_kong_phd_fellowship_scheme) and the HKU Presidential PhD Scholar Programme (gradsch.hku.hk/prospective_students/fees_scholarships_and_financial_support/hku_presidential_phd_scholar_programme). During the study period, the candidate has chance to conduct research in our collaborator’s lab (e.g. Mayo Clinic in USA) for one year.
For RA applicant: the candidate should intent to apply for PhD program in the group within 1-2 years period.
The candidate will
1. Develop algorithms, databases and web servers for bioinformatics methodology development in the above two areas.
2. Develop methods to integrate (single-cell) multiple OMICs data (eg ChIP-seq+RNA-seq, RNA-seq+WGS) for function inference.
3. Work with our collaborators for NGS analysis pipeline development and result interpretation.
1. Master or bachelor degree in Quantitative Sciences (Bioinformatics, Computer Science, or Biostatistics etc.) with some biology knowledge, or PhD/MS in Biomedical Sciences with programming experience (python or R).
2. Can work collaboratively and independently.
3. Experience with two or more of the following key words is preferred: ChIP-seq, RNA-seq, WGS, WES, PCA, gene regulatory networks, genetic variants annotation/prioritization, deep learning, machine learning, data mining.