Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
the complex food composition, which can lead to masking effects and molecular interactions in the food matrix. The applicant will work on the development of machine learning prediction models
-
knowledge in the field of machine learning, in particular deep neural networks Practical experience in the application of machine learning algorithms for both regression and classification problems Excellent
-
candidate to join our team to contribute to a project which will focus on the development of machine learning (ML) architectures for predicting and designing enzymatic reactions. To create the ML framework
-
Data, geodata) Data visualization, georeferencing and web mapping (e.g. D3.js, open source GIS, R, Shiny)Programming, testing and documentation (e.g. Python, R, Jupyter, git) Machine learning and
-
methods (NLP) as well as machine learning in combination with symbolic logic are applied. ISE research relies and extends on knowledge representation standards developed for the Semantic Web. ISE research
-
, programming and experience with machine learning are advantageous. We expect an interest in seagoing work and independent data acquisition in the coastal zone of the Baltic Sea. What does the IOW offer? The IOW
-
, survey) or applied microeconometrics, and applied economics. You have experience with big data and machine learning methods? This would be a particular asset! With excellent English language skills, both
-
, the candidate will work on integrating methods of statistics / causal inference with methods of machine learning with applications in epidemiology. We seek an excellent, open-minded and team-spirited
-
tool for agricultural datasets based on merging advanced statistics, machine learning and biophysical modelling regular interaction with the FAIRagro team to develop appropriate infrastructure
-
possible. She/he will contribute to ifo’s main research topics with his/her independent research applying a combination of state-of-the-art machine learning and causal inference methods to innovative and