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greenhouse gas emissions, nutrient losses, and water quality. Though traditional statistical methods are easier to perform, they have less statistical power and accuracy to predict FE complex in dairy cattle
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amplicons using high throughput technologies (e.g. Illumina MiSeq); bioinformatic and statistical analysis of sequencing outputs; analysis of concentration and quality of available soil carbon (physical and
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data analysis methodologies including: Experimental design, advanced statistical methodology, machine learning, mass spectrometry data, molecular biology, cell cultures, bioactivity assays. The student
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related to biological sciences with knowledge of biochemistry, molecular biology, genetics and statistics, and an interest in plant breeding. General practical experience in a biochemical or genetic
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their scientific, statistical, business and academic skills. The student will also have the opportunity to present their work at national and international conference such as the IX International Postharvest
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generic PhD student training in project and time management, scientific writing skills, statistics and data management, and presentation skills. FBS2021-53-Magan: Post-harvest control and mechanisms
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the inspection but also post-processes the data providing a statistical output with confidence. The PhD The ability to develop a fully automated inspection system that is capable of fully charactering the damage
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programming, and R statistical software at Cranfield University. Training will be provided both by the supervisory team and using CENTA training courses. The student will also be encouraged to gain broader
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Application deadline11 Jan 2021 Award type(s)PhD Start date09 Nov 2021 Duration of award3 years EligibilityUK, EU, Rest of World Reference numberSWEE0128 Entry requirements The statistical analysis skills
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be provided in Python and R for data science, statistical analysis and modelling by the supervisory team. There will be opportunities to attend various other trainings, short courses and seminars