澳大利亚科廷科技大学博士后职位—数据可视化与分析

澳大利亚科廷科技大学博士后职位—数据可视化与分析

Research Associate / Research Fellow

Curtin University of Technology

Description

The Centre for Crop and Disease Management at Curtin University brings together university expertise in data science, geographical information systems, farming systems, agribusiness, and actuarial science. We have strong industry partners and focus on research to overcome key challenges in the horticulture and broadacre agricultural industries.

The Centre for Crop and Disease Management (CCDM) at Curtin are partnering with CSIRO Agriculture and Food and CSIRO Data61, jointly developing important digital technologies to address new problems in the agricultural sector. Data61 is the data and digital specialist arm of CSIRO and home to one of the largest collections of research and development expertise in Artificial Intelligence (AI) and data science in the world, hosting cutting-edge facilities including the Mixed Reality Lab, Robotics Innovation Centre and AI4Cyber Enclave. You will you have the chance to work with staff from CSIRO and Curtin University to address industry related problems with big data.

To learn more about this opportunity, please contact Dr Julia Easton, Project Lead by email or on +61 0403 311 395

Your new role

You will use data capture, data visualisation and data analytical skills to address industry related problems. You will combine and integrate complex sources of data to develop data science driven solutions that help agricultural producers solve real world problems. Data streams available for the agricultural sector include information from proximal sensors, data loggers, remote sensing imagery, industry and ground surveys. You will use proximal or remote sensing applicable to agriculture or biological systems and be able to use modern analytic platforms such as Python or R.

You will also bring your experience in data processing, data management and data visualisation to solving industry related problems and have a willingness to communicate statistical results to non- statisticians and industry representatives.

We are looking for someone with a PhD in Applied Statistics, Mathematics, Computer Science, Biological Modelling, or an equivalent field.

Candidates should also portray an established publication track record in relevant fields.

Candidates with experience in data visualisation and analytics expertise are encouraged to apply.