Sort by
Refine Your Search
-
Listed
-
Employer
- SciLifeLab
- University of Lund
- Umeå University
- KTH Royal Institute of Technology
- Swedish University of Agricultural Sciences
- Chalmers University of Technology
- Lunds universitet
- Örebro University
- Karlstad University
- Linköping University
- Blekinge Institute of Technology
- Karolinska Institutet (KI)
- Nature Careers
- Mälardalen University
- Sveriges lantbruksuniversitet
- Linnaeus University
- University of Gothenburg
- Lulea University of Technology
- Jönköping University
- KTH
- Karlstads universitet
- European Magnetism Association EMA
- Stockholms universitet
- Umeå universitet
- University of Borås
- Uppsala universitet
- 16 more »
- « less
-
Field
-
communication systems for 5G and 6G, channel modelling, channel characterization, radio-based positioning and sensing, and associated signal processing algorithms. Work duties Employment as an assistant professor
-
to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout your studies, you will be
-
these transcripts into protein sequence databases. Guide the development of proteogenomics through implementation of novel algorithms and computational analysis infrastructure Development of tools to support clinical
-
between these duties varies over time. During the employments three initial years, the employee is offered 30% of full time for competence development, which may be used for own research and other
-
-based positioning and sensing, and associated signal processing algorithms. Work duties Employment as an assistant professor is a tenure track position, which aims for the holder to develop
-
acclimate to a changing world and how we can breed better plants. About the position In this project you will develop and apply statistical and genetic models: Research-focused work on creating and using
-
these transcripts into protein sequence databases. Guide the development of proteogenomics through implementation of novel algorithms and computational analysis infrastructure Development of tools to support clinical
-
with machine learning and generative AI algorithms, with working knowledge of deep learning frameworks such as PyTorch or TensorFlow is considered a strong advantage. • Extensive experience in multi
-
which research in Resistance Biology, Integrated Plant Protection and Chemical Ecology develops the sustainable use and management of biological resources. Read more about the Department and Chemical
-
lifecycle management. At the same time, the project delves into software design concerns, focusing on the internal structure and evolution of AI-enabled components themselves, including the design of