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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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range of research areas and design an individual research portfolio with high impact. As such, successful candidates will be able to align the skills that they learn pursuing a doctorate with their
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data streams offered by techniques such as high-throughput sequencing of genomes and biomes, continuous recording of video and audio in the wild, high-throughput imaging of biological specimens, and
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sensors, communicating over networks, to achieve complex functionalities, at both slow and fast timeframes, and at different safety criticalities. Future connectivity of the next generation of multiple
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and coordinate with growers, collaborators, and research staff across multiple locations. - Maintain research records and assist with data analysis and reporting. Minimum Qualifications: - Ph.D. in
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such as cell isolation methods using microfluidics or microwell devices, preparation of sequencing libraries from ultra-low quantities of nucleic acids have enabled the characterisation of DNA, RNA and
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closely align with the profile of the ideal candidate, even if not all criteria are fully met. If you believe your experience and skills broadly match the description, we would be pleased to hear from you
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Ph.D. and why the Experimental Soft Matter Physics group aligns with your career goals. While AI can help with language correction, we discourage using it to write the letter itself, as this may result
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beneficial – but not mandatory – if applicants demonstrate alignment with one of our research centres (described above) or faculty research strengths. We offer A fully funded position with access
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mutualistic and antagonistic insect flower visitors in the greenhouse and in the field. Analyse complex data sets involving e.g. metabarcode sequencing Chemical analysis of flower nectar using HPLC and GC-MS