Post-doctoral Fellow, School of Biological Sciences
Work type: Full-time
Department: School of Biological Sciences (26000)
Categories: Academic-related Staff
Applications are invited for appointment as Post-doctoral Fellow (3 posts) in the School of Biological Sciences (Ref.: 513937), to commence on September 1, 2022, or as soon as possible for one year, with possibility of renewal, subject to satisfactory performance and funding availability.
Applicants should possess a Ph.D. degree in Agronomy, Ecology, Forestry, Earth system science, Geography, Remote sensing, or related fields, and a track record of publications. They should have experience in GIS, biophysical remote sensing, multivariate statistical analysis, and/or process-based modeling and model-data fusion. Strong quantitative and programming skills (e.g. Python, R, Fortran, or Matlab) and prior experience in supercomputing, big data analytical systems, or Google Earth Engine are essential as the appointee will deal with big remote sensing data and/or numerical modeling.
The appointee will work on one of the following research projects:
- Crop physiology and climate-smart water use: To understand the molecular and ecophysiological mechanisms underlying plant water regulation; develop novel multi-scale remote sensing techniques for real-time monitoring of soil water content, crop water use, stress level, and health conditions; explore the linkage between plant water stress and crop yield; develop data-driven smart diagnosis system to guide optimal irrigation schedule; and develop novel data-model fusion approaches for modeling crop yield, water use, and environmental feedbacks under both current and future climatic conditions.
- Novel climate-smart systems for sustainable agriculture: To formalize and integrate intensive field- and experiment-based knowledge into numerical models; leverage field and remote-sensing observations for model calibration and evaluation; develop novel data-model fusion system for upscaling, real-time monitoring, forecasting, and advising the optimal use of fertilizer and water in agroecosystems; utilize the calibrated models to predict future crop yield, assess environmental impacts, and suggest optimization strategies both in response to seasonal forecast and under different climate change scenarios. This would also explore models of sustainable intensification to determine how to meet proposed commitments within the draft Post-2020 global biodiversity framework.
- Co-benefits of biodiversity and ecosystem services for Earth’s sustainability: To analyze the patterns and drivers of flora and fauna diversity over large landscapes; elucidate the adaption mechanisms of terrestrial species diversity to global changes in high diversity ecoregions. Explore proximate linkages among environment, biodiversity, and ecosystem multifunctionality; predict the impacts of various global changes on biodiversity and important ecosystem services and ecosystem functions; suggest policy and management/conversation plans for optimizing the co-benefits of biodiversity and ecosystem services under global climate change.
For all the projects above, the successful applicant will be supervised by Professor Jin Wu (plant ecophysiology and remote sensing; email: email@example.com). For Project 1 and 2, the applicant will be jointly supervised by two professors from the Chinese University of Hong Kong, Professor Hon-Ming Lam (Agrobiotechnology; email: firstname.lastname@example.org and Professor Amos Tai (Earth system science and land-atmosphere interactions; email: email@example.com), and also Dr. Kun Zhang (ecohydrology and land surface modeling; email: firstname.lastname@example.org). For project 3, the applicant will be jointly supervised by Professor Alice Hughes (biodiversity, conservation, and species distribution modeling; email: email@example.com) and Dr. Mizanur Rahman (mangrove ecology and ecosystem multifunctionality; email: firstname.lastname@example.org).
A highly competitive salary commensurate with qualifications and experience will be offered, in addition to annual leave and medical benefits.
The University only accepts online application for the above posts. Applicants should apply online and upload an up-to-date C.V., a cover letter, and contact information of three references via email to Professor Jin Wu at email@example.com Review of applications will commence as soon as possible and continue until July 31, 2022, or until the post is filled, whichever is earlier.