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skills (Python preferred). Familiarity with ML/Data Science frameworks: PyTorch, JAX, Hydra, MLflow, Pandas (or similar). Additional qualifications Experience with project management, planning and
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R and Python, specifically Experience with GIS and spatial data analysis Experience with natural language processing or text-as-data approaches Familiarity with large-scale survey data, conflict and
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spatial analysis and mapping tools (e.g., QGIS, ArcGIS, or spatial packages in R/Python) Interest or experience in applying AI or machine learning methods to ecological questions Personal attributes: Strong
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dynamics, numerical modeling, and scientific programming is required. The following areas of expertise are considered beneficial: Experience in scientific computations using Python, C, C++. Experience in
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of supervisors that covers both academic pursuits. Primary tools are the programming language Python to exploit its advanced deep learning toolboxes (e.g., Keras, TensorFlow, and PyTorch), alongside
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biology, molecular biology including mammalian cell culture is required Documented knowledge in bioinformatics and programming (Python, R) is required Experience in LC-MS and mass spectrometry is required
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biochemistry are required Profound knowledge in bioinformatics, especially Python and/or R are required Experience from relevant research projects investigating cellular metabolism, and/or protein modifications
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devices Knowledge of Python programming Good knowledge of materials technology, and basic knowledge of environmental assessment of materials Good written and oral English skills PLEASE NOTE: For detailed
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in quantitative methods (reflected in courses and/or research experience) Proficiency in R, Python, or similar programming languages (or strong skills in another statistics software) Knowledge about
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, Python or similar). Knowledge of European standards for the design of buildings (Eurocodes) Ability to handle big datasets Oral and written presentation skills in Norwegian or another Scandinavian language