Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
description You will identify, visualize and characterize bacterial and archaeal cells associated with iron minerals by combining fluorescence in situ hybridization (FISH) and correlative imaging, DNA- and/or
-
related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
-
deep learning, computer vision, medical image analysis or unsupervised learning is an advantage. English language skills, both written and spoken Qualification requirements PhD stipends are allocated
-
natural language processing (NLP) is highly desirable. • Experience or education in health data science or a health-related field is a plus. • Good Python programming skills to implement and prototype
-
1.1.2027 or as soon as possible. Job description You will be contributing to/establishing/developing an in-situ imaging system for NH3. You will be further developing optical NH3 sensors in the laboratory
-
to the operation, development, and maintenance of laboratory infrastructure across the department. The position involves collaboration with researchers, students, and technical staff in a broad range of experimental
-
Postdoc in Digital Education and Empowerment for Patients with Atrial Fibrillation and Comorbidities
compared with usual care. The postdoc will coordinate and contribute to the co-design process, prototype and program development, feasibility test and evaluation of the effectiveness of the AF-EMPOWER
-
independent way. Have an interest in AI and technology Can communicate effectively, both in writing and verbally, in English and Danish. Nice to have: Experience in graphic design and image editing (e.g. Figma
-
, data management and analysis (under supervision) Performing research tasks within the area of classical archaeology, e.g. Literature searches and image processing Supporting processes in connection with
-
-gas emissions using a hyperspectral camera. We are currently focusing on methane. The work will include processing and analysing hyperspectral observations and developing and validating methods