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Field
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with a wide range of data formats and engaging with data experts and database managers. The second major focus is advanced data analysis and statistical modeling to identify patterns in fish distribution
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, a research component and a teaching component. In terms of research, you will be expected to: Develop and implement a coherent and original programme of high-quality empirical research commensurate
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degree in Computer Science, Math, Statistics or Engineering programs. Ph.D would be an asset. Knowledge of classification algorithms, vision-language models (VLM) and Hugging Face Transformers is an asset
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? Then consider advancing these theories with us. In this project, we aim to extend the powerful tools of statistical mechanics on graph and network models to broader applications in soft and active
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Fully Funded PhD Research Studentship tax-free stipend of £20,870 Design, Informatics and Business Fully Funded PhD Research Studentship Project Title: Behaviour-Based Anomaly Detection
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State University of New York University at Albany | Albany, New York | United States | about 7 hours ago
Administration and Policy and (2) Faculty Affiliate with the Information Science Ph.D. Program. Primary Responsibilities: Preparation of research proposals Literature reviews Empirical fieldwork (collection
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about to obtain, a First or Upper Second-Class UK Honours degree, or the equivalent qualifications gained outside the UK, in Statistics, Mathematics, Data Science or Computer Science. To apply, please
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training in computational tools and statistical methods over the course of the project. The project includes placements at NPL and Waters-TA Instruments, with opportunities to work in state-of-the-art
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Applications are invited for a Senior Researcher in Decision Analytic Modelling, working with Associate Professors Apostolos Tsiachristas and Brian Nicholson, on a research programme developing and
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techniques to map gene regulatory networks (e.g. ChIP-seq, RNA-seq) and statistical approaches to discover genotype-phenotype associations (e.g. GWAS, random forest) in common-garden and aquaculture