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need expert knowledge in bioinformatic data analysis. Strong expertise in multi-omics data analysis (using R and Python) and a deep understanding of machine-learning models are must-criteria
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analysis and processing of large analytical-chemical data sets. Experience and knowledge of digital teaching and evaluation strategies for large amounts of data (such as programming languages Python and/or R
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: PhD degree in analytical, biological, food, or computational chemistry, biotechnology or related field Experience in mass spectrometry (especially GC-MS) and programming (e.g. R), statistical knowledge
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Language skills: English, German Knowledge of statistical programming with R and experience with GIS are required Desirable skills and qualifications Experience with laser scanning data is desirable Ability
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spectrometry is advantageous, though not required Familiarity with proteomic sample preparation, R scripting, and previous experience as a lab technician or in lab management are all considered a plus What we
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(quantitative research methods and advanced proficiency in statistical software such as Mplus, R, etc.) • Teaching experience/experience in e-learning • Experience in student supervision • Excellent
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of local affiliates and forge strong scientific partnerships with internal and external partners. Closely liaise with Commercial, Market Access and R&D to demonstrate the medical value for marketed products
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Didactic skills / experience in e-learning Skills in experimental work with babies Programming skills (Matlab) Advanced knowledge of statistics (R) Experience with multiverse analysis and open science
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of bioanalytical chemistry • Expertise on data analysis with R or Python tools. Experience in processing of targeted and untargeted mass spectrometry datasets • Demonstrated research competence and initiative
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the laboratory Experience in the most commonly employed techniques in the laboratory (see "Your future tasks" section) Programming skills in python and R with experience in statistical data analysis