Postdoctoral Research Fellow

Employment location: Zhongshan Ophthalmic Center in Guangzhou

Work locations: Zhongshan Ophthalmic Center in Guangzhou and Centre for Eye Research Australia in Melbourne

Salary: Competitive salary package, AUD 80-100K per annum plus bonus and benefits

Working Hours: Full Time (1.0 FTE)

Employment Time: Fixed-Term available for 2 years

1. POSITION SUMMARY

The position is for a postdoctoral research fellow who is pursuing a career as an independent ophthalmologist, epidemiologist or biostatistician. This position is primarily to coordinate and manage research projects within both the University of Melbourne and Sun Yat-sen University. The overall objective of the position is to work on a “monozygotic twins digital human being”, a deep data project similar to NASA Twin Study(https://www.nasa.gov/twins-study/), the Google Baseline Study (https://medicine.stanford.edu/annual-report-2018/the-project-baseline-study.html) and Pioneer 100 Wellness Study (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568837/)except we are using monozygotic twins as participants when their genetic background is matched.

The research fellow would be required to work on existing and future datasets generated by the team. State-of-the-art machine learning techniques or investigations into new theoretical and practical approaches will be used to achieve accurate behavior recognition based on 3-axis accelerator data and head positioning sensor data, and to analyze the differences among twins. The Research Fellow will be under supervision of Prof. Mingguang He (a Professor of Ophthalmology in both University of Melbourne and Sun Yat-sen University) and co-supervised by computer science and data analytics experts. The incumbent will be required to work in close collaboration with researchers in in Australia and internationally. This is a fantastic opportunity for a research fellow to build their research profiles on leadership development, skills on analyzing large scale data, as well as publishing papers in high impact journals.

2. RESPONSIBILITIES

• Independently develop strategies to ensure effective and efficient research management.
• Contribute to the preparation of data management and data analysis plans.
• Undertake data management and data analysis, including application of advanced statistical techniques to large, complex datasets.
• Prepare research grant proposals, tenders for commissioned research, scientific papers, protocols and conference abstracts.
• Independently design and undertake research projects using population and linked datasets.
• Present research findings at meetings, workshops and conferences.
• Attend meetings associated with research projects or work of the organisational unit at departmental and/or faculty meetings and/or relevant committees.
• Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on the health and safety of yourself or others.

3. SELECTION CRITERIA

3.1 Essential Criteria

• PhD in biostatistics, epidemiology, public health, computer science, psychology or a related discipline
• Sound understanding of theory and methods relating to the design of epidemiological studies and the statistical analysis of health-related data.
• Demonstrated experience in the management and analysis of large complex health datasets and the analysis of linked, longitudinal data.
• Demonstrated ability to write analysis plans
• A track record of publications and conference presentations relative to opportunity.
• Experiencein supervising undergraduate students in research.
• Excellent interpersonal and communication skills, with proven ability to build successful working relationships with a variety of people
• Ability and willingness to work independently and as part of a team
• Knowledge of health and safety responsibilities and commitment to attending relevant health and safety training

3.2 Desirable Criteria

• The ability to conduct independent research with limited supervision in machine learning and statistics.
• Demonstrated ability to conceptualize novel research questions in areas relevant to public health or health services research, and to develop these into research outputs.

4. About Us

Professor Mingguang He is the Professor of Ophthalmic Epidemiology at the University of Melbourne, Principal Investigator at Centre for Eye Research Australia and Principal investigator at the Zhongshan Ophthalmic Center, Sun Yat-sen University.

He undertook his medical training in China, holds a Master degree in Public Health from Johns Hopkins University in Baltimore, and PhD in ophthalmology at Moorfields Eye Hospital in London.

Professor He is a global expert in vision-related clinical and epidemiologic research. He received numerous funding from NHMRC, MRFF, Google and other National Natural Science Foundation of China that supported several landmark studies in both China and Australia. His research work has led to more than 200 peer-review papers including original article published in JAMA (2015) and the Lancet (2019).

He was awarded NHMRC investigator grant and honored as NHMRC Leadership Fellow in 2019. He serves editorial board for several important journals, including Ophthalmology, PLoS One, Molecular Vision and APJO. He is currently the deputy secretary-general of Asia-Pacific Academy of Ophthalmology.

His research interests include clinical and epidemiological research, randomized clinical trials, twin studies and innovative technology. His current research priority is big data and precision medicine.

5. How to apply

There is no expiration date for this advertisement. Interested applicants are invited to submit the following materials via email to 

Professor Mingguang He, MD PhD FRANZCO (mingguang.he@unimelb.edu.au)

Dr Xianwen Shang, Postdoc fellow (xianwen.shang@unimelb.edu.au)

1. CV (includes your basic personal information, educational and professional background, major academic achievements/awards, research project experience)
2. A list of your published papers/patents
3. A cover letter
4. Responses to the Key Selection Criteria