106 parallel-processing-bioinformatics positions at University of Adelaide in Australia
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of Computer and Mathematical Sciences is home to world class expertise working to solve some of the most challenging societal problems in pioneering ways. We have course offerings across two disciplines
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The Graham Matheson Scholarship for Postgraduate Research Studies in Mineral Processing, Mining Engineering or Chemical Engineering is a prestigious scholarship established through a generous
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% superannuation applies. Fixed term, full time position available for 24 months. The Mangiola Group at SAiGENCI, seeks a highly motivated Postdoctoral Fellow to lead the development of advanced bioinformatic tools
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members Commitment to the principles of equity, diversity and inclusion. Desirable characteristics: Understanding of bioinformatics. Experience with HPAEC-PAD and HPLC systems. The path to Adelaide
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internally across the University community. Willingness to supervise PhD, Masters and/or Honours students. Desirable Knowledge and skills in bioinformatics for analysing metagenomes and microbial genomes
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cancers. Our laboratory uses cutting edge methods (multi-omics, single-cell, genome editing as well as contemporary pre-clinical model systems) and bioinformatics to understand how sex hormone receptors and
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herbicide and antimicrobial resistance that threatens the global agricultural and health industries. This exciting project will draw on parallels with drug resistance to investigate a new molecular mechanism
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recycling: Project 1 (2 PhD students): Development and optimisation of DES battery recycling process - These projects aim to improve the DES-based battery recycling processes, focusing on investigating
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one time. Initiate and lead a process of review, updating methodologies in line with developing science or updates to infrastructure Propose acquisitions of new physical and software infrastructure
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finite element methods, which demand extensive data and are costly, PINNs embed governing physical laws directly into the learning process. This allows effective management of limited and noisy data