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instruments, with data obtained with DNA methods and data obtained with a Hirst trap. • Numerical models used by the group covers the particle dispersion model HYSPLIT in combination and the numerical models
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computational methods for analysing spatial omics data work with interdisciplinary collaborators to apply methods to real biological data and interpret results contribute to the supervision and mentoring of PhD
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organising seminars and conferences, and winning further funding to underpin the research. If appropriate, the role may involve acting as a formal co-supervisor for research students. The post holders will
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EXPERIENCE in: Scientific/Academic writing Research methodology (Quant or Mixed Methods) Experience with statistical software (e.g., R, Mplus, SPSS, etc.) Credentials must be obtained prior to the start date
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, plus demonstrable experience of quantitative research methods and dissemination of findings. Training for all aspects of the role will be provided. If you are still awaiting your PhD to be awarded you
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increasingly autonomous and agentic models. The research will examine frontier AI systems that interact with operating systems, APIs, software tools, other agents, and complex environments, moving beyond text
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a PhD in biology, earth system or data science, or a similar field, and have several years of experience with interdisciplinary collaborations focused on understanding biodiversity dynamics by
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(MRO), as well as interpretation of results and collaboration with CEMol teams and partner institutions. Mandatory requirements: PhD in Materials Science or related fields; proven experience in
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. Teamwork: Ability to work collaboratively with others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications
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of technical standards and legislation. Authorship and co-authorship of patents, registrations of intellectual property rights over software, mathematical methods, and rules for mental activity. Participation in