Research Fellow in Statistical Omics

**Research Fellow in Statistical Omics**:
**Position Number**: 0064027
**Location**:Parkville
**Role type**:Full-time; Fixed-term for 2 years
**Faculty**:Faculty of Science
**Department/School**:School of Mathematics and Statistics
**Salary**:Level A.6 - $105,518 p.a. plus 17% super
- **Develop advanced statistical methods for integrating omics data to enhance biological understanding.**:

- **Collaborate with top experts across statistics, computational biology, and biology to drive interdisciplinary research and career growth.**:

- **Salary packaging, subsidised health and wellbeing services, fitness and cultural clubs, Myki discounts, and a 25% discount on graduate courses to our staff and their immediate families**

**About the Role**
Join the School for Mathematics and Statistics and Melbourne Integrative Genomics in a dynamic role as a Research Fellow, focusing on pioneering statistical method development for omics data integration.

You will innovate new computational and statistical methods, fostering campus-wide collaborations.

This is a rare opportunity to thrive in a collaborative environment alongside statisticians, bioinformaticians, and biologists.

Your responsibilities will include:

- Contribute towards the research effort of the team and to develop your research expertise with an increasing degree of autonomy.
- Under the guidance and support of Senior Academic staff conduct internationally competitive research, resulting in publications in high impact journals.
- Contribute to and publish academic papers and other scholarly outputs to a high academic standard in accordance with the research expectations of the University of Melbourne
- Actively participate in research seminars and conferences to disseminate research findings as opportunities arise.
- Contribute to the preparation, or where appropriate individual preparation of research proposal submissions to internal or external funding bodies as relevant.

**Who We Are Looking For**

You will also have:

- A PhD or equivalent research higher degree in statistics, or interdisciplinary computational statistics research in genomics or a related area.
- Strong computer programming skills in R and experience in software development.
- Experience in multivariate statistical analysis.
- Knowledge of mammalian molecular biology and genomics

For further information regarding responsibilities and requirements, please refer to the attached PD.

**Your New Team - “Melbourne Integrative Genomics (MIG)"**

Melbourne Integrative Genomics (MIG) is a cross-disciplinary initiative at the interface between biology, mathematics and statistics at the University of Melbourne.

MIG is a leading institution where we use innovative mathematical and computational approaches to answer pressing questions in biology and biomedicine. MIG, which was founded in 2017, fosters a vibrant environment for collaborative research and education.

**What We Offer You**
In addition, we offer the opportunity to be part of a vibrant community and enjoy a range of benefits, including generous leave provisions, salary packaging, health and well-being services and discounts on graduate courses. For more information, check out our benefits page

**About the University of Melbourne**
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**Aboriginal and Torres Strait Islander Applicants**
We aspire to be the University of choice for Indigenous Australians, with unprecedented investment to attract, nurture and retain Aboriginal and Torres Strait Islander students and staff. Tangible support through a range of programs and initiatives will ensure that you personally succeed and flourish while at the University of Melbourne.

**Join Us**
- **Resume**:

- **Cover Letter outlining your interest, experience and the responses against the five following Selection Criteria (max 2 pages)**:

- Experience in developing computational and statistical methods for omics data integration
- Experience in analysing omics data, either in a collaborative multi-disciplinary context or for methodological development purposes
- Experience in developing R packages
- Experience in mentoring students
- Experience in teachi