14 molecular-modeling-or-molecular-dynamic-simulation Fellowship positions at University of Adelaide
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plant molecular physiology for major crops in South Australia. Outputs from this investment will lead to new research discoveries related to fundamental understanding of molecular biology, physiology and
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Technology (SET) This position plays a vital role in developing advanced theoretical tools and models for superconducting quantum materials research, contributing to leading-edge defence-related technologies
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contribution of 17% superannuation applies. Fixed term position for 24 Months. Postdoc opportunity - Open for Applications Until Filled. We are seeking a dynamic and motivated Postdoctoral Fellow in Ecological
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molecular genetics supporting the Grains Research and Development Corporation funded Weed Management Initiative under the supervision of Professor Christopher Preston at the University of Adelaide. As a
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decision making in contested and dynamic environments, considering a broad range of modelling and simulation and software engineering research approaches. The ideal candidate will enjoy working in a team
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characterization. Expertise in the development and application of in-situ or operando techniques to investigate interfacial phenomena at the molecular or atomic scale is essential. The role requires an individual
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Sciences, Plant Molecular Biology, Plant Synthetic Biology, Plant Biochemistry or related subject. Demonstrated skills in plant molecular biology and biochemistry technique, including plant transformation
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quantitative methodologies, especially for instance in the areas of econometrics (microeconometrics), statistics, and economic modelling. Demonstrated knowledge of statistical and econometrics software packages
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and modelling. The Postdoctoral Research Fellow will need to have the ability to conduct field studies on plot size assessments, outstanding analytical and problem-solving skills, research, design
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closely with an industry partner, you will generate cutting-edge insights into protein structures and protein-ligand interactions using in silico approaches such as bioinformatics, modelling and docking