Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
-supervise MSc/PhD students and contribute to the dissemination of results through publications and conferences Qualifications As a formal qualification, you must hold a PhD degree (or equivalent) in
-
PhD degree in Computer Science, Electrical Engineering or equivalent. Research interests and a scientific track record in Edge Computing research fields, such as Embedded AI, Edge AI, TinyML, and AIoT
-
A full-time position as research assistant or postdoc (37 hours/week) is vacant across the Center for Integrated Multi-omics in Precision Medicine (CIMP) and the Danish Spatial Imaging Consortium
-
: Programming skills (Python, and/or C# or similar programming language). Knowledge of some of the following fields: medical image data, database structure, image processing, creation of user-friendly WEB pages
-
, cellular biophysics or optical instrumentation. Responsibilities and qualifications We imagine that one of our new colleagues has experience in construction and/or operation of home-built optical setups
-
structure quantification by tomography and imaging Perform testing across different scales, i.e. characterizing the viscoelastic properties of the base material and the nonlinear mechanics of the scaffolds
-
setups. Build and Experiment : Lead the hands-on development, calibration, and testing of the prototype diagnostic system in our lab and at leading international fusion facilities. Collaborate : Work
-
approaches are particularly encouraged to apply. Qualifications - Relevant university education and PhD degree - Relevant background – this could be microbiology, molecular biology, cell biology, imaging
-
an experience in technology-assisted monitoring or computational image analysis. Expected start date and duration of employment The position will start in June 2026, with exact starting date as agreed between
-
electroluminescence and photoluminescence imaging, preferably daylight and field-based methods. Proven skills in data analysis, image processing and machine learning. Experience with PV performance modelling, power