Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
GIScience, geoinformatics, spatial data science, spatial analytics, or a related field; experience with diverse spatial analytical methods; strong programming skills (e.g., Python) and version control
-
, urban analytics, geoinformatics, or a related field; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python
-
engagement and participatory research with quantitative system modelling of our research group; experience with systems modeling and computer programming (e.g. Python); strong communication and scientific
-
Max Planck Institute for Psycholinguistics | Nijmegen, Provincie Gelderland | Netherlands | about 1 month ago
background, with experience in one or more programming languages (e.g. R, Python, Perl, or shell scripting) Desirable experience includes : Structural equation modelling (e.g. lavaan) Meta-analysis methods
-
assessment. Programming and data-analysis skills in a reproducible scientific workflow, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work
-
Monte Carlo techniques and relevant programming languages will be an asset. You should have good interpersonal and communication skills and should be able to work in a multicultural environment, both
-
). Experience in multi-modal data integration for prioritizing disease-specific targets: combining quantitative multi-omics approaches (es. RNA-seq, Ribo-seq, proteomics, immunopeptidomics). Strong programming
-
models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as PyTorch. You enjoy interdisciplinary work: you will
-
programming techniques; modelling and simulation of radiation effects on complex semiconductor components for radiation hardening; and software engineering practices. Basic knowledge of component
-
transformers, self-supervised learning, foundation models, autoencoders or related architectures; • strong programming skills in Python and experience with a deep-learning framework such as PyTorch