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Field
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class honours degree in an appropriate subject or a relevant Masters qualification. Suitable disciplinary backgrounds include chemistry, analytical chemistry, environmental science, materials science
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to solve research problems In addition for Research Associate Awareness of the research environment High level of analytical and problem solving capacity Ability to communicate complex information with
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information storage. However, most DNA storage systems remain passive: data are written, archived, and read. This PhD project will help pioneer a new generation of dynamic DNA data storage systems capable not
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international equivalent, in computer science, artificial intelligence, data science, human-computer interaction, psychology, organisational psychology, business analytics or a closely related subject. A relevant
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Studentship Information Supervisor: Prof Rumiana Ray (University of Nottingham) Secondary Supervisor: Dr Hadrien Peyret (University of Nottingham), Dr Dong-Hyun Kim (University of Nottingham), Prof
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in programming for data analysis and algorithm development (e.g. Python, MATLAB). Strong analytical skills and the ability to critically evaluate technical and scientific literature. Excellent
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, Economics, Business Analytics, Data Analytics, Energy Finance, Accounting, or a related field is desirable. Experience with empirical research methods and programming languages such as Python, R, Stata
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, but its human burden is badly understood. This PhD addresses this gap, integrating multiple high‑value datasets describing metagenomic and metatranscriptomic sequencing information, clinical and
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, analytical chemistry and enzymology. Working in an enthusiastic and supportive team the student will become expert in state-of-the-art (bio)chemistry, biophysics and photocatalysis. They will also expand
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ownership of the project, shaping experimental design, developing new approaches, and driving the research with increasing independence. By integrating laboratory, analytical, and field-based methods