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: prior technical project management experience and excellent communication skills in English; expertise in Artificial Intelligence based Computational Fluid Dynamics frameworks; knowledge of physics
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satisfactory performance and funding availability). The Department provides an open, supportive, dynamic and motivating academic environment with the possibility to work on the cutting-edge research project
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. Preference will be given to those with experience in handling human iPSC-based cell- and/or organoid- platforms. The appointee will join a young and dynamic research group working independently and
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technical skills in next generation sequencing, including library preparation and bioinformatics analysis. Experience in developing bioinformatics pipeline and maintaining computer server would be
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analysis, and proficiency in statistical and computer modelling software (e.g. R, Python, Matlab, and C++) would be advantageous. The appointee will work with a research team to study the methodologies
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, fluent in written and spoken English, and competent in basic computer database management. Familiarity or experience with gene sequencing or gene manipulation will be an advantage. The appointee will be
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the possibility of renewal subject to satisfactory performance. Applicants should have a Ph.D. in bioinformatics, genetics, computational biology or other relevant disciplines, and in-depth experience with at least
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strong sense of responsibility and be able to work independently and in a team with different stakeholders. The appointee will work on a research project that evaluates the effects of a programme designed
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Bioinformatics, Computing/Programming, or a related discipline. Experience in using PMNN, ESM2 and RFdiffusion would be an advantage. The appointee will work in collaboration with research teams focusing
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Science or equivalent, with 3 years’ related work experience, or a Ph.D. degree in a relevant discipline; (ii) solid statistical and computing skills; (iii) effective communication skills in both written