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Basic knowledge of programming (preferably Python; R or MATLAB also accepted with willingness to switch) Experience in quantitative data analysis Interest and/or experience in landslide research
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personality: A completed Master's degree in Data Science, Physics, Chemistry, Computational Biology, Bioinformatics, or a related field. Strong programming skills in Python, R, or similar languages. Experience
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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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of teleconferences / project meetings / workshops / conferences. In project proposals preparation: monitoring of suitable European R&D&I funding schemes; proposals structuring, commenting; collection of information
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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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, human-computer interaction, public health, or a related field. Quantitative research skills, including data analysis with SPSS, R, JASP, jamovi or similar software. Experience in planning and conducting
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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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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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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