Position Description	

College/Division:	College of Health & Medicine	
Faculty/School/Centre: 	Research School of Population Health	
Department/Unit: 		
Position Title: 	Biostatistician / Applied Statistician	
Classification:	Academic Level B 	
Position No:	TBA	
Responsible to:	Biostatistician Level C	

PURPOSE STATEMENT:
The Research School of Population Health (RSPH) at The Australian National University (ANU) is a leading school of population health in Australia. RSPH researchers have a tradition of excellence in addressing the world's most pressing population health issues, including achieving and maintaining good mental health, healthy ageing, chronic disease prevention, infectious disease prevention, determining environmental risks to health, improving health services, social and cultural determinants of health, and health for the global population.

The Biostatistician / Applied Statistician will contribute to the School through research in biostatistics and/or applied statistics such as econometrics, contributions to competitive research grants, supervision of research students, and participation in the School’s teaching program.

KEY ACCOUNTABILITY AREAS:

Position Dimension & Relationships: 
The Biostatistician / Applied Statistician reports to the Biostatistician level C and will contribute to activities across RSPH. This position will work in partnership across a range of disciplines within RSPH, as well as actively developing national and international collaborations.

Role Statement:
Specific duties required of a Level B Academic may include:
•	the conduct of research complementary to the existing research profile of the School, including the application of innovative methods for population health research;
•	the production of high impact research with a view to publishing original and innovative results in refereed journals;
•	the supervision or co-supervision of research students as appropriate;
•	participation in delivery and evaluation of statistics education in the School;
•	expertise in methods across one or more areas of longitudinal modelling, mixed methods research, econometrics and modelling, meta-regression, and knowledge discovery from data;
•	collaboration with research groups across the School;
•	undertaking administrative functions primarily connected with the area of research, including the preparation of research proposals and pursuing funding applications;
•	undertaking professional activities including, subject to availability of funds, attendance at conferences and seminars in the field of expertise;
•	participation in outreach activities including with prospective students, research institutes, industry, government, the media and the general public.

Skill Base
A Level B Academic will normally have completed a relevant doctoral qualification or have equivalent qualifications or research experience. In addition evidence of research ability will be based on publications, conference papers, reports or professional or technical contributions.	

SELECTION CRITERIA:
1.	A PhD in biostatistics, econometrics or applied statistics with a strong record of achievement as evidenced by publications in peer reviewed journals.
2.	Demonstrated experience in the application of biostatistics, econometrics or applied statistics to population health research.
3.	Highly developed oral and written communication skills and a demonstrated ability to develop positive relationships with students and colleagues at all levels including implementing research that will lead to innovative, multi-disciplinary interactions across the School.
4.	Ability to apply for competitive research grants or fellowships.
5.	Ability to contribute to collaborative interdisciplinary teaching and to community outreach and a commitment to collegiality.
6.	Ability to contribute to the supervision of higher degree research students.
7.	A demonstrated understanding of equal opportunity principles and policies and a commitment to their application in a university context.

Supervisor Signature:		Date:	2 May 2018	
Printed Name:	Alice Richardson	Uni ID:	U3767151	

References:	
Academic Minimum Standards