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programme combining colloid science, nano-bio interfaces, robotics, and data-driven experimentation • Significant scientific freedom to shape research directions, methodologies, and platform development
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German Cancer Research Center (DKFZ) Heidelberg • | Heidelberg, Baden W rttemberg | Germany | 2 months ago
interdisciplinary, which is reflected by the fact that PhD students have an academic background in (molecular) biology, (bio-)chemistry, (bio-)physics, mathematics, computational biology, computer
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electrochemical CO2 reduction and electrochemical upgrading of bio-based compounds. Be part of change Your tasks include working with electrochemical cells. The evaluation of electrochemical performance is
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Gesellschaftswissenschaften (KIGG) The Inter-University Doctoral Programme in Economics (MAGKS) Circular economy of urban carbon flows through innovative bio-waste recovery pathways (CirCles) Graduate School for Moving Images
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biology, bio-technology, or related fields Strong expertise in pluripotent stem cell culture and differentiation Interest in standardized and automated cell culture systems Solid experience in Python and
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Degree PhD Course location Bremen Teaching language German English Languages Courses are held in English and German. PhD candidates can choose to write their thesis in English or German. Programme
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language English Languages English Full-time / part-time full-time Programme duration 6 semesters Beginning Only for doctoral programmes: any time Application periods This programme has no deadline listed
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an integrated subject consisting of bio-, eco- and geoinformatics in addition to scientific computing. By using the tools of informatics in this subject, anyone can study or model objects, structures, regulatory
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spectrometry. ProteomicsDB (https://www.proteomicsdb.org/) is an internationally well-reputed publicly available database that provides information about proteins and other bio-molecules initially centered
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, (Bio-)Informatics, Computer Science or related disciplines Strong background in modeling multi-modal data (images, tables, text, etc) Understanding of biases and causal inference Experience with machine