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effort between School of Engineering and School of Chemical Engineering at Aalto University supported by our industrial partners. The PhD student to be jointly supervised by two supervisors; Prof. Hamid
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findings to academic and industrial audiences, publish in leading journals, and actively contribute to the development and dissemination of open-source software. Additionally, you will support junior
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, a PhD (or have equivalent experience). Candidates with a background in environmental or related sciences are particularly encouraged to apply, but we will also consider those with other numerical
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autonomous sensing systems. The project requires experience with setting up sensing hardware, software defined radio systems and other lab equipment for data collection in addition to experience of programming
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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data science and machine learning Additional software skills such as Shiny, LaTeX, Tidyverse, Tableau, C/C++, Java, GitHub Experience in report writing for projects underpinned statistics Attributes and
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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• Skilled in prototyping and experimental investigations for marine vehicles • Skilled in using mainstream CFD and autonomous system softwares (e.g. Star-CCM+, OpenFoam) • Research experience in
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, epigenomics and transcriptomics from these models alongside extensive human tumour collections. You will be PhD-qualified, or have submitted your PhD thesis for examination at the point of commencing this post