Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
-edge ecological monitoring techniques, big data analysis, and creative science communication. The centre provides access to extensive global datasets, fostering collaboration across disciplines and
-
, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation
-
that can be used for training machine learning and deep learning models. You will work in tight collaboration with other researchers in Nijmegen, Delft and at the Hubrecht Institute (van Oudenaarden group
-
., machine learning, stochastic dynamic programming, simulation). Affinity with (food) supply chain management is preferred. To collaborate with and to co-supervise MSc thesis students and internship students
-
adaptation of state-of-the art machine learning codes to deal with redshift distortions, intrinsic (galaxy) biases, survey selection biases and in particular the complications encountered in photometric
-
that activity-silent mechanisms, such as short-term synaptic plasticity, also play an important role. We will experimentally target these two mechanisms, using EEG in combination with machine learning to reveal
-
days off. With full-time employment, you can choose between 30 or 41 days of annual leave instead of the statutory 20. Additional employment conditions Work and science require good employment practices
-
guidelines and advice. Possesses good organizational skills and perseverance. Demonstrates competencies such as conceptual ability, presentation, planning, and monitoring progress. Our working conditions are
-
of the largest migrant languages in the Netherlands (e.g., Turkish, Arabic, Tigrinya, Ukrainian) or motivation to learn the language at a receptive level is recommended. Our working conditions are in accordance
-
observations. Your major challenge is in model development, and there is room for you to develop machine learning applications in the field of firn modelling. If successful, your work will lay the foundation