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Field
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codes is essential. Experience with modelling conjugated organic molecular-based systems (e.g. electronic structure, charge transport) would be particularly highly valued. Experience in coding with Python
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in R or Python Candidates that have successfully obtained competitive, extramural funding during their doctoral studies are preferred. Knowledge, Skills and Abilities: Excellent written and verbal
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modelling; strong programming and research engineering ability (Python with modern ML tooling such as PyTorch/JAX) and good software practices; familiarity with interactive/agentic settings (e.g., tool-using
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imaging data, preferably using Python, and hands-on experience building bespoke laboratory setups for imaging experiments investigating alloy composition or relevant applications. You will have a strong
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in carrying out the planned research. Below is listed experience and skills that will be considered: Proficiency in statistical and programming languages such as Perl, Python, and/or R. Experience
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, functional genomics, cell biology, and cardiovascular physiology. Experience or interest in programming languages such as R or Python. Independence to lead a project as well as willingness to work in a team
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pipelines and interfaces): Python (numpy, scipy, pandas, PyQt5, matplotlib, pympi.Elan, torch, etc.), R/RStudio, automatic speech processing systems (e.g., Nemo, MFA), and NLP packages (such as spaCy
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of Python and basic experience with traffic simulation tools (e.g., SUMO, VISSIM). Research FieldTechnology » Transport technologyYears of Research Experience4 - 10 Additional Information Benefits As provided
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Multi-omics integration Mass spectrometry-based metabolomics NGS Data Analysis Programming proficiency in R or Python Training and Mentoring Junior Scientists Strong scientific communication Excellent
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and Edge Computing Good programming skills (e.g., Python, MATLAB, C++) and experience with system simulation. Experience with industrial field projects or familiarity with DCS/MES systems is preferred