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Field
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the analysis of multimodal spatial omics data across multiple projects, collaborating closely with experimental biologists. Main tasks and responsibilities: Develop and implement robust computational pipelines
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the use of bioinformatics tools for metagenomic and transcriptomic data analysis (e.g., QIIME, DADA2, R, Python). Demonstrated ability to independently design and conduct experiments, analyze data, and
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, characterisation and modelling to study and generate a new understanding of MoSS. These advances will have applications across multiple sectors, including pharmaceuticals, agrochemicals, and food industries
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research outputs. The candidate will need to demonstrate agility in managing and leading multiple projects and work independently in this ever-changing and fast-paced sector. The position is funded by CAR, a
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, students, and external partners. Contribute to teaching, mentoring, and curriculum development. Knowledge, Skills, and Abilities Strong background in AI, GNC, and SDA. Demonstrated proficiency in C++, Python
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++, Python, MATLAB, and modern machine learning frameworks. Proven research record, including peer-reviewed publications. Excellent communication and collaboration skills. Minimum Qualifications Ph.D. in
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, Prof Anton van den Hengel and his research team to publish research outputs. The candidate will need to demonstrate agility in managing and leading multiple projects and work independently in this ever
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part-time employment basis. The successful candidates will conduct research and develop products under multiple Eratosthenes Centre of Excellence projects funded by the European Union, including
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analysis (e.g., R, Python, GraphPad) Research and Analytical Abilities: Experimental design and troubleshooting Complex problem solving and critical thinking Data interpretation and utilization Knowledge
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mass and heat transfer physics would be ideal, but is not required; You have laboratory experimental experience; You have programming experience, knowledge of Python and Git is a plus; You have a proven