Skip to main content

Research Associate / Research Fellow (Marine Remote Sensing) The University of Western Australia.






Research Associate / Research Fellow (Marine Remote Sensing) The University of Western Australia


Research Associate / Research Fellow (Marine Remote Sensing)
Job no: 505000
Work type: Full time
Location: Crawley, Perth CBD
Categories: Science
Faculty of Science
Indian Ocean Marine Research Centre
Fixed term 2 year appointment, full-time basis
Salary range: Level A $70,936 p.a. – $95,464 p.a. or Level B $100,374 p.a. – $118,776 p.a. plus superannuation
The University of Western Australia (UWA) is ranked amongst the top 100 universities in the world and a member of the prestigious Australian Group of Eight research-intensive universities.  With an enviable research track record, vibrant campus and working environments, supported by the freedom to 'innovate and inspire' there is no better time to join Western Australia's top University.
About the team
The Indian Ocean Marine Research Centre (IOMRC) is a collaboration between the University of Western Australia (UWA), the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australian Institute of Marine Science (AIMS), and West Australia Department of Primary Industries and Regional Development.
The ICoAST project involves all IOMRC partners and will focus on several sites along Western Australia's coast including World Heritage listed Shark Bay. The project has three dedicated research themes focusing on: remote sensing of physical processes in shallow marine habitats, remote sensing of benthic habitats, and molecular ecology.
About the opportunity
Under the supervision of the Remote Sensing of Physical Processes Research Theme leads, Dr Jeff Hansen and Dr Paul Branson, this position will focus on:
Evaluating and developing satellite remote sensing methods to measure bathymetry in optically deep waters.
Contribute to the development of a low-altitude unmanned aerial vehicle (UAV) that fuses data from multiple sensors to accurately, routinely and cost-effectively measure bathymetry.
Investigate the opportunities to use novel time- and space-resolved drone measurements to observe wave and hydrodynamic processes over complex benthic habitats.
You will work in both local and remote fieldwork sites to collect ground truthing datasets, test new hardware, develop algorithms and machine-learning methods. This position will also offer you the opportunity to work closely with research staff across all research themes to integrate the remote sensing techniques to achieve broader project goals. You will also provide supervision and assist with the training of research students.
To be considered for this role, you will demonstrate:
PhD in Remote Sensing, Oceanography, Ocean Engineering, Mechatronics or related discipline
Relevant research experience in the development or application of remote sensing algorithms
Experience with data analysis using software such as Python or Matlab
Experience in preparing manuscripts for publication and giving presentations at conferences
Highly developed interpersonal, written and verbal communication skills
Ability to work independently, show initiative and work productively as part of a team
About you
To be successful in this position, you will possess experience in supervising and training undergraduate or postgraduate research students. You will be flexible and willing to participate in field activities involving overnight trips to remote locations.
A valid, or ability to obtain, a C Class driver's license and CASA Remote Pilots Licence (RePL) will also be required for this position.
Full details of the position responsibilities and the selection criteria are outlined in the position description.  In preparing your application you are asked to demonstrate clearly that you meet the selection criteria.
Please see the position description prior to applying: 📷 Position Description - Research Associate or Fellow (Marine Remote Sensing).pdf
Closing date: Tuesday,  20 October 2020
This position is open to international applicants.
Application Details: Please apply online via the Apply Now button.
Our commitment to inclusion and diversity
UWA is committed to a diverse workforce. We celebrate inclusion and diversity and believe gender equity is fundamental to achieving our goal of being a top 50 university by 2050.
We have child friendly areas on campus, including childcare facilities. Flexible work arrangements, part-time hours and job sharing will all be considered.
UWA has been awarded Platinum Employer Status for being a Top Ten Employer for LGBTI Inclusion by the Australian Workplace Equity Index (AWEI -2019).






Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://www.facebook.com/Applied.Geography
http://geogisgeo.blogspot.com

Comments

Popular posts from this blog

History of GIS

The history of Geographic Information Systems (GIS) is rooted in early efforts to understand spatial relationships and patterns, long before the advent of digital computers. While modern GIS emerged in the mid-20th century with advances in computing, its conceptual foundations lie in cartography, spatial analysis, and thematic mapping. Early Roots of Spatial Analysis (Pre-1960s) One of the earliest documented applications of spatial analysis dates back to  1832 , when  Charles Picquet , a French geographer and cartographer, produced a cholera mortality map of Paris. In his report  Rapport sur la marche et les effets du choléra dans Paris et le département de la Seine , Picquet used graduated color shading to represent cholera deaths per 1,000 inhabitants across 48 districts. This work is widely regarded as an early example of choropleth mapping and thematic cartography applied to epidemiology. A landmark moment in the history of spatial analysis occurred in  1854 , when  John Snow  inv...

GIS data continuous discrete ordinal interval ratio

In Geographic Information Systems (GIS) , data is categorized based on its nature (discrete or continuous) and its measurement scale (nominal, ordinal, interval, or ratio). These distinctions influence how the data is collected, analyzed, and visualized. Let's break down these categories with concepts, terminologies, and examples: 1. Discrete Data Discrete data is obtained by counting distinct items or entities. Values are finite and cannot be infinitely subdivided. Characteristics : Represent distinct objects or occurrences. Commonly represented as vector data (points, lines, polygons). Values within a range are whole numbers or categories. Examples : Number of People : Counting individuals on a train or in a hospital. Building Types : Categorizing buildings as residential, commercial, or industrial. Tree Count : Number of trees in a specific area. 2. Continuous Data Continuous data is obtained by measuring phenomena that can take any value within a range...

History of GIS

1. 1832 - Early Spatial Analysis in Epidemiology:    - Charles Picquet creates a map in Paris detailing cholera deaths per 1,000 inhabitants.    - Utilizes halftone color gradients for visual representation. 2. 1854 - John Snow's Cholera Outbreak Analysis:    - Epidemiologist John Snow identifies cholera outbreak source in London using spatial analysis.    - Maps casualties' residences and nearby water sources to pinpoint the outbreak's origin. 3. Early 20th Century - Photozincography and Layered Mapping:    - Photozincography development allows maps to be split into layers for vegetation, water, etc.    - Introduction of layers, later a key feature in GIS, for separate printing plates. 4. Mid-20th Century - Computer Facilitation of Cartography:    - Waldo Tobler's 1959 publication details using computers for cartography.    - Computer hardware development, driven by nuclear weapon research, leads to broader mapping applications by early 1960s. 5. 1960 - Canada Geograph...

Disaster Management

1. Disaster Risk Analysis → Disaster Risk Reduction → Disaster Management Cycle Disaster Risk Analysis is the first step in managing disasters. It involves assessing potential hazards, identifying vulnerable populations, and estimating possible impacts. Once risks are identified, Disaster Risk Reduction (DRR) strategies come into play. DRR aims to reduce risk and enhance resilience through planning, infrastructure development, and policy enforcement. The Disaster Management Cycle then ensures a structured approach by dividing actions into pre-disaster, during-disaster, and post-disaster phases . Example Connection: Imagine a coastal city prone to cyclones: Risk Analysis identifies low-lying areas and weak infrastructure. Risk Reduction includes building seawalls, enforcing strict building codes, and training residents for emergency situations. The Disaster Management Cycle ensures ongoing preparedness, immediate response during a cyclone, and long-term recovery afterw...

Data Generalization in GIS

Data generalization in GIS is the process of simplifying complex geographic data to make it suitable for visualization and analysis at specific map scales. It reduces unnecessary details while preserving the overall patterns and essential characteristics, ensuring that the map remains clear and interpretable at different zoom levels. Key Concepts and Terminologies Purpose of Data Generalization : To simplify spatial data for better visualization and usability at smaller scales. To prevent maps from becoming cluttered or unreadable due to excessive detail. To maintain the essence of geographic features while omitting minor details. Example : On a world map, a small island may be represented as a single point or omitted, while on a local map, it may appear with detailed boundaries. Key Data Generalization Techniques Simplification : Definition : Reduces the number of vertices or points in a line or polygon, removing minor details while retaining the general shap...