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completed both the baseline and follow-up questionnaire to undertake a 1-to-1 interview (online or in person) focused on satisfaction with the materials and future recommendations. Descriptive statistics will
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), singular optics, using electrons, atoms and light and the exploration of complex systems using statistical field theory. "Catastrophes on order-parameter manifolds" (with Dr Alexis Bishop and Dr Timothy
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Status: Closed Applications open: 1/07/2024 Applications close: 18/08/2024 View printable version [.pdf] About this scholarship Description/Applicant information Project Overview The project will examine emotional processing during Emotion Focused Therapy (Watson & Sharbanee, 2022; Greenberg &...
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. Eligibility criteria We seek a highly motivated PhD student with the following qualifications: A bachelor's or master's degree in computing or mathematics with research experience. Proficiency in programming
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part of their Australian PhD program students seeking to complete a full PhD program in the US postdoctoral candidates seeking to do research professionals (with 10 years' relevant experience) seeking
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I supervise a wide range of projects at the intersection of photonics and nanotechnology, investigating how we can efficiently control light on the nanoscale. Applications are in areas such as optoelectronics, green energy, and fundamental quantum optics. As a member of my group you will have...
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candidate. The PhD project will focus on data analytics, data mining, and statistical modelling of complex biological system in crops. The project will have access to large volume of state-of-the-art Next
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statistical competence in quantitative methods. They will have a demonstrated ability to work independently and to appropriately manage sensitive and confidential information. Responsibilities may include
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tools to record and derive important contextual information. The student will also learn relevant statistical techniques such as Linear Mixed Modelling to compare between drills and competition
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models that can forecast the likely outcomes of current practices. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term