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by the Baden-Württemberg Medical Association. Furthermore, the prerequisites to obtain the education authorization in ophthalmology as well as postdoctoral qualifications and teaching experience
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Responsibilities: Planning a study to investigate cakes with different ingredient ratios, including baking the cakes Planning and conducting in vitro digestion experiments in the laboratory Preparing samples
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newly appointed professors with various types of support, such as welcoming services and assistance for dual career couples. The LGL is a member of the ‘Success Factor Family’ network. LMU Munich and the
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Max Planck Institute for Medical Research, Heidelberg | Heidelberg, Baden W rttemberg | Germany | 3 days ago
and battery technology. The place of work will be in Stuttgart and Heilbronn. Your tasks direct collaboration with PhD students and postdocs on cutting-edge research fabrication of novel metal fiber
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ASAP (2 x 3-year non-tenure track appointments). We are looking for well-trained and outstandingly accomplished early career scientists (i.e., MD, PhD or MD/PhD plus 2 to 8 years of postdoctoral training
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CCMs. The CCM is the core component of every electrolyzer. This is where electrical energy is converted into chemical energy in the form of hydrogen gas. For our group "Electrolysis", we are looking
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profile You have an excellent Ph.D. and postdoctoral track record in the natural or life sciences, with an interest in the broader field of molecular systems biology. Applicants with a background in
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Senior Scientist / Group Leader on Bioinformatics / Computational Biology on RNA Regulation in Disea
for extramural funding and build an own computational biology research group Your profile: A PhD (or equivalent) in Bioinformatics / Computational Biology More than 5 years postdoctoral experience with several
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the amount of tedious and error-prone manual work. The driving factor is the availability of large amounts of data. However, in this domain data is often sparse or labelling data is expensive. This requires
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the amount of tedious and error-prone manual work. The driving factor is the availability of large amounts of data. However, in this domain data is often sparse or labelling data is expensive. This requires