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pathways driving leukemic transformation during haematopoietic development. The successful candidate will use in vitro differentiation systems (ESC/iPSC) to model normal and malignant haematopoiesis
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: autonomous and fault-tolerant systems (including health monitoring systems), advanced guidance, control, estimation and optimisation techniques and tools, and the technology development of GNC sensors with a
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and how it evolves. In particular we focus on the evolution and evolvability of vertebral counts, and we use various species of Lake Malawi cichlids as our model organism. To address these questions, we
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Criteria: Qualifications A good first degree in Mathematics, Physics or a related subject. A PhD (or be close to submission) in Applied Mathematics, Solar Physics, or a related subject. Experience Experience
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in a group with a strong publication track record Work in a supportive, international environment just outside Copenhagen If you want to apply your skills in animal models and translational
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academic career in a group with a strong publication track record Work in a supportive, international environment just outside Copenhagen If you want to apply your skills in animal models and translational
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! Education: PhD degree on Computer Science and Engineering, Telecommunication Engineering, Applied Mathematics or Statistics with application or specialization in Data Science. Required experience and skills
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Screen reader users may encounter difficulty with this site. For assistance with applying, please contact hr-accessibleapplication@osu.edu . If you have questions while submitting an application
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for integration into diagnostic tools Preparing manuscripts for submission to both medical and machine learning journals Qualifications Candidate profile: Required: PhD in mathematics, statistics, data science
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Engineering, Mathematics, Statistics, or related fields. • Strong programming skills in Python, Java, C++, etc. • A solid foundation in generative AI, machine learning, and related areas. • An Interest in eye