Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
strong background in machine learning, computer vision, or data-driven modeling. You have extensive experience in the development and implementation of AI and machine learning algorithms, ideally with
-
strategies in psychiatry. This research combines recent advances in machine learning and cognitive neuroscience to contribute to future clinical tools for diagnosing and monitoring neuropsychiatric disorders
-
background in data sciences we ask: Insights in the most suitable data science techniques (e.g., machine learning, cluster analysis) to answer specific research questions based on available data as a basis for
-
such as data science, AI, computer science, machine learning, Earth system science, climate etc., with a thesis subject relevant to the description of the tasks outlined above. Additional requirements In
-
for this position, the following is required: PhD in a relevant field such as data science, AI, computer science, machine learning, Earth system science, climate etc. with a thesis subject relevant to the description
-
strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners on design optimization, life-cycle analysis, and business case
-
Village to calibrate and validate models. Investigating control strategies (e.g. predictive or machine learning approaches) to improve performance and reduce costs. Collaborating with industrial partners
-
difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
-
difficult and the creation of more intelligent process control strategies and innovative methods of tracking reliability can be achieved with expert informed machine learning techniques, which offer more
-
). The emergence of data-driven techniques (broadly grouped under the term “machine learning”) challenges the traditional foundations of controls and represents an alternative paradigm that cannot be ignored