Senior research fellow - data analyst

This Job is based in Australia

• One of Australia’s leading research & teaching universities
• Vibrant campus life with a strong sense of community & inclusion
• Enjoy a career that makes a difference by collaborating & learning from the best

At UNSW, we pride ourselves on being a workplace where the best people come to do their best work. The School of Biotechnology and Biomolecular Sciences is a preeminent life sciences education and research hub with the broad aims to excite, educate, inspire and advance knowledge in molecular biosciences to address real-world challenges and create opportunities. The Research Fellow (Level B)/Senior Research Fellow (Level C) will join our Centre for Ecosystem Science at UNSW. The role will contribute to a project developing new knowledge products to support national strategies for ecosystem protection, management and restoration, utilizing their strong background and advanced analytical and spatial data skills. About The Role

• Level B ($123k - $145k) Level C ($150K - $172K) plus 17% Superannuation and annual leave loading
• Fixed Term – 5 years
• Full-time (35 hours per week)

The role of Research Fellow/Senior Research Fellow reports to Professor David Keith and has no direct reports.. LEVEL B: Specific responsibilities for this role include:

• Engage in individual and/or collaborative research in a manner consistent with disciplinary practice.
• Be accountable for development of analytical methods, workflows and data streams to support a consistent national framework for ecosystem data synthesis using the IUCN Global Ecosystem Typology.
• Develop diagnostic workflows to identify drivers, threats, key components and indicators of ecosystem function, structure and composition.
• Develop analytical tools for estimating rates of ecosystem change and spatial indicators required to assess levels of threat to ecosystems.
• Analyse trends in properties and spatial distribution for specific ecosystem types from multi-modal time series data, including satellite imagery, survey data, biodiversity data repositories, citizen observations and ground-based images. Apply state-of-the-art methods to these analyses, such as cloud-based remote sensing, spatio-temporal modelling and Artificial Intelligence (AI) to interpret trajectories.
• Contribute to design, delivery and support of novel ecosystem training and development initiatives for government, community and industry.
• Create scholarly impact in the discipline which is recognised by peers in the advancement of disciplinary knowledge.
• Work closely with project partners and collaborators to co-design, implement and publish high quality research.
• Conduct research/scholarly activities under limited supervision, either independently or as a member of a team (as per the norms of the discipline).
• Establish a personal research portfolio and start developing independent research proposals.
• Contribute to the development of applications for competitive funding under the guidance of senior colleagues.
• Participate as co-investigator or chief investigator in competitive grant applications, or show evidence of active participation in research collaborations funded by competitive grants.
• Design research projects.
• Mentor and guide students and colleagues and develop the next generation of academics through involvement in supervision of HDRs (as per the norms of the discipline).
• Align with and actively demonstrate the Code of Conduct and Values
• 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 psychosocial or physical health and safety of yourself or others.
• Develop research groups in ecology and conservation science and research methods that are appropriate to those disciplines.

LEVEL C: (in addition to the above)

• Make independent contributions to research that have a significant impact in ecosystem ecology and conservation science and create a nationally recognised research track record.
• Attract peer recognition and establish research network/s (based on the norms of the discipline) at national level.
• Obtain research income from nationally competitive research grants (and/or research fellowships) and research end-users as a member or leader, at or above the level that is relevant to ecology and conservation science in leading universities.

About The Successful Applicant (Selection Criteria) LEVEL B: To be successful in this role you will have:

• A PhD in ecology, conservation science or a related discipline, and/or relevant work experience.
• Proven commitment to proactively keeping up to date with ecosystem science knowledge and developments.
• Demonstrated track record in research with outcomes of high quality and high impact with clear evidence of the desire and ability to continually achieve research excellence as well as the capacity for research leadership.
• Well-developed computational and statistical skills, with experience in spatial analysis and/or time-series analysis and modelling of ecological data using R, Python or other programming languages.
• Well-developed skills in the management of large ecological data sets.
• Familiarity, and preferably experience with ecosystem risk assessment and classification frameworks and standards
• Proven capacity for successful collaboration and world-class research translation, with demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.
• A track record of significant involvement with the profession and/or industry.
• High level communication skills and ability to network effectively and interact with a diverse range of students and staff, with demonstrated ability to work in a team, collaborate across disciplines and build effective relationships.
• Evidence of highly developed interpersonal and organisational skills.
• An understanding of and commitment to UNSW’s aims, objectives and values in action, together with relevant policies and guidelines.
• Knowledge of health & safety (psychosocial and physical) responsibilities and commitment to attending relevant health and safety training.

LEVEL C: (in addition to the above)

• Advanced computational and statistical skills, with experience in spatial analysis and/or time-series analysis and modelling of ecological data using R, Python or other programming languages.
• Advanced skills in the management of large ecological data sets.
• Evidence of highly developed interpersonal and organisational skills.

You should systematically address the selection criteria listed above in your application. Please apply online - applications will not be accepted if sent to the contact listed. Contact: David Keith E: david.keith@unsw.edu.au Applications close: January 6th, 2025________________________________________ Find out more about working at UNSW at UNSW is committed to equity diversity and inclusion. Applications from women, people of culturally and linguistically diverse backgrounds, those living with disabilities, members of the LGBTIQ+ community; and people of Aboriginal and Torres Strait Islander descent, are encouraged. UNSW provides workplace adjustments for people with disability, and access to flexible work options for eligible staff. The University reserves the right not to proceed with any appointment.