16 professor-computer-"https:"-"https:"-"https:"-"I.E" PhD positions at Nature Careers in Germany
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, (bio)informatics, and multimodal data analysis. The research group focusses on the mechanisms of Hypothalamic-Pituitary-Gonadal (HGP) axis regulation that governs human reproduction. The group
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-01-01), together with leading researchers across Europe. You will become part of a cohort of 13 PhD students jointly trained in modern biophysical techniques involving both computational and
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Call for applications We are pleased to announce the call for the second cohort of our Graduate Programme RNAmed – Future Leaders in RNA-based Medicine. Applications are invited for 11 PhD
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Job Id: 11716 Fixed term of 3 years | Full-time with 100% | Salary according to TV-L E13 | Institute of Medical Informatics We are UKM. We have a clear social mission and, with our focus
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Job Id: 11712 Fixed term of 3 years | Full-time with 100% | Salary according to TV-L E13 | Institute of Medical Informatics We are UKM. We have a clear social mission and, with our focus
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Dynamics (MBD) department contributes, using computational methods, to the development of personalized microbiome-based strategies to aid in the detection, monitoring, treatment, and prevention of human
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communication skills in English are mandatory German speaking skills are not required This is a wet-lab position, so applicants with a purely (bio)informatics background will not be considered. WE OFFER: Salary
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interdisciplinary research in molecular, structural, and cell biology as well as in physiology, biophysics, epi /genetics, (bio)informatics, and multimodal data analysis. In this project, we will elucidate
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the course of your doctoral program Our requirements Solid basic knowledge of cell culture as well as isolation of human primary cells Interest and experience in working with bioreactors, especially organ-on-a
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, (bio)informatics, and multimodal data analysis. The research group led by Dr. Johanna Raidt focuses on the identification of known and novel MMAF- and PCD gene variants using large patient cohorts