Sort by
Refine Your Search
-
Employer
-
Field
-
have: A PhD in electrical engineering, energy engineering, mechanical engineering, control engineering, operations research, applied mathematics, or a closely related field. Documented experience in
-
-Chem • You will be contributing to the development of machine learning models used on data from Poleno Jupiters, applying Python and machine learning. • The position will focus on implementing
-
need to have a PhD in marketing, consumer behaviour, psychology, behavioural economics, environmental psychology, or another relevant field. Demonstrated experience designing, fielding and analysing
-
of Prof. Georg Madsen, with regular shorter research stays at Aarhus University. The project combines density functional theory (DFT), machine-learned force fields and atomistic simulations to uncover how
-
as part of a running team including two PhD students. Your profile Applicants should hold a PhD in molecular biology, genetics, epigenetics, developmental biology, or a closely related field
-
the development of new research directions at the department. Your competencies You hold a PhD degree in Electrical Engineering, Control Engineering, Electrochemistry or a closely related field or can document
-
a PhD in biology, earth system or data science, or a similar field, and have several years of experience with interdisciplinary collaborations focused on understanding biodiversity dynamics by
-
of the project in collaboration with national and international partners. The position is research-oriented but may involve teaching assignments. Qualifications Candidates must hold a PhD relevant to the academic
-
and supervision of students at the bachelor's, master's, and PhD levels. Qualifications for the postdoctoral position Academic qualifications at PhD level in animal or veterinary sciences. Research
-
genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods