Sort by
Refine Your Search
-
Organisation Job description We are seeking a candidate for a PhD project on the philosophical aspects of data science and data science use, with specific attention for the use of data science
-
at uncovering how the capacity for Darwinian evolution may have first arisen. While parts of this puzzle have been solved, an important open question is the emergence of information transfer (inheritance), one
-
PhD position - Modelling the emergence of information transfer in prebiotic self-replicating systems
how the capacity for Darwinian evolution may have first arisen. While parts of this puzzle have been solved, an important open question is the emergence of information transfer (inheritance), one
-
results, further research is guided by trial and error with the goal of deriving intuitive trends. Data-driven approaches are attractive alternatives. Descriptors are used to characterize the molecular
-
Master’s degree in Data Science, Artificial Intelligence, Computational Linguistics, Computer Science. Has excellent academic writing and oral skills in English. Has experience with large language models
-
analyzing experimental data. Has demonstrable affinity with the topic of sustainable consumer behavior. Has excellent communicative and project management skills to handle the multiple stakeholders involved
-
. Has experience with qualitative and/or quantitative research methods. Has excellent communicative and project management skills to handle the multiple stakeholders involved in the project (e.g
-
that span and integrate multiple scientific domains. We are looking for candidates with strong expertise in their respective fields and a passion for interdisciplinary collaboration. Each project will not
-
: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
-
: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create