9 genetic-algorithm Fellowship research jobs at The University of Queensland in Australia
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opportunities via the academic promotions process. About You Possess (or be in the process of obtaining) a PhD or equivalent in plant breeding or genetic mapping or statistical genetics. Demonstrated ability
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opportunities for accelerating genetic gain prior to real-world implementation. This project is delivered in collaboration with Cobb-Vantress Inc. and funded through the Cobb Research Initiative. The successful
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frameworks (MOFs), and related materials using hybrid classical-quantum algorithms. A key component of the role involves using first-principles methods that capture strong electronic correlations, such as DFT
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of classical and hybrid classical-quantum algorithms for treating the correlations. This position offers exciting opportunities for collaboration within UQ, across the QDA network, and with external research
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programming and data analysis. Interest in developing methods, algorithms or software. Evidence of publications in high-quality peer-reviewed journals. Excellent communication skills. Experience
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the gap between gene discovery and practical breeding outcomes in crop science. This role offers the chance to work at the forefront of plant genetics, contributing to real-world advancements in agriculture
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, plant physiology, and molecular genetics Experience in feed quality, protein/starch assays, or plant cell wall chemistry is advantageous but not essential. Demonstrate a track record of the effective
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will undertake genetic/genomic analyses for trait discovery and molecular breeding and will grow your research profile to achieve national recognition in your discipline. The position will be based at St
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on clusters and high-performance computing infrastructure), Information Retrieval methods, Machine Learning algorithms, wrangling large-scale datasets, and showcasing the research results. The ability to work