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) Experience with plant biochemistry, genetics and physiology Experience with bioinformatics and coding in Python or other programing language Experience with protein software tools like AlphaFold3, Boltz2
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@au.dk) Applicants must have a relevant PhD degree in biology, biogeochemistry, hydrology, glaciology, oceanography, geoscience or physics. Field experience, data analysis and programming (e.g., python
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SD-26065 -POST-DOC IN METHOD DEVELOPMENT FOR HIGH RESOLUTION CHARACTERIZATION OF NOVEL SAFE AND S...
in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? Describe the main responsibilities
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studying neural circuits Familiarity with programming languages (e.g. R, Python) and an ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and
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, transformer-based models), including experience with their application to biomedical and biological data; Experience with machine learning frameworks and programming languages (e.g. Python) for handling large
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applications Good analytical and (bio)statistical skills Knowledge of relevant programming languages such as Java, Python, and Perl Good knowledge of relational and document-oriented database design (e.g., MySQL
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, reproducible data handling and analysis workflows in R and/or Python; author reusable packages and pipelines Collaborate across DKFZ programs; co-supervise students; contribute to grant applications Publish in
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(e.g., R, Python). Proven ability to publish at a high international level. It is a prerequisite that you are good at communicating in English. Strong collaborative skills and good collaboration skills
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and Python are required. The successful candidate will be based in Odense, under the primary supervision of Prof. Stefan Jänicke. The appointment will be made for 2 (two) years at a competitive salary
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learning approaches for high-dimensional data, and programming skills in R or Python. Profile Track 2 – Experimental Immunology / Bone Marrow Biology / Trained Immunity Candidates with an experimental