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. Person Specification PhD (or near to completion or equivalent experience) in a relevant field, including statistics, mathematics, computer science, epidemiology. Strong mathematical and quantitative skills
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to grant proposals, and present findings at international conferences. What you bring: PhD (or near completion) in Bioinformatics, Computational Biology, Data Science, Statistical Genomics, or related field
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research programme at King’s, focussed on establishing a competitive research niche and positioning them to apply for intermediate-level post-doctoral fellowships to consolidate their careers, from Research
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in English is provided. Application Requirements for Both Positions: All applicants must have obtained a PhD degree within the last 10 years. Please submit the following documents to the ICYS
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and beyond. Candidate Profile We welcome applicants with diverse backgrounds in experimental or computational biology who are excited by pioneering research directions. Qualifications PhD in molecular
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projects that leverage our optical expertise to probe brain function Preferred Qualifications & Expertise: PhD in neuroscience, bioengineering, computational biology, or related field At least one strong
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Research Fellow (Fusion Shielding Materials) - School of Metallurgy and Materials - 105638 - Grade 7
a framework for the role. Person Specification or Required Knowledge, Skills, Qualifications, Experience Hold a PhD (or one near to completion) in a relevant area, such as Fusion Energy, Nuclear
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Supervise students on research-related work and provide guidance to PhD students where appropriate to the discipline Contribute to developing new computational models, techniques and methods Undertake
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* Contribute to the supervision of PhD students and junior researchers Your Profile: * PhD in Bioinformatics, Computational Biology, Systems Biology, Biostatistics, or a related field – (Doctoral degree should
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organoids will be plus. Dry lab: Highly motivated candidates with a PhD/MD degree in bioinformatics, genome science, systems biology, biomedical informatics, computational biology, machine learning, data