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charge of: · Developing LCI models and using LCA to assess different scenarios of energy storages in batteries, as well as the realization of preliminary LCAs for novel substances
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for motivated individuals skilled in computer science/computational biology/bioinformatics with the desire to make a difference for people suffering from mental health problems. A Masters Degree in (Bio
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different ion activation methods affect peptide fragmentation, including work with a next-generation multi-mode trap instrument supporting both collisional- and electron-based dissociation Contribute
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
quality. Secondly, different machine learning strategies based on traditional supervised learning techniques (e. g. random forest (RF), artificial neural network (ANN)) will be applied using the parameters
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Knowledge and experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical methods in the context of biological systems Experience with programming (Python, Perl
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utilizing state-of-the-art approaches such as: In vitro and ex vivo cell culture, ability to work with different type of primary and stable cells, ability to create knockout or knock in CRISPR/cas9 is plus
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. Strong programming skills in R and/or Python are essential, as well as prior experience in data analysis, statistics, or machine learning. The project involves large-scale single-cell and spatial
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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specific focus on cost-effectiveness, emission reduction, and social acceptability. The candidate will be involved in various (inter-)national initiatives and engaged with different political decision makers