Sort by
Refine Your Search
-
Country
-
Employer
- Karolinska Institutet
- Chalmers University of Technology
- Harvard University
- Institute of Biosciences, University of São Paulo
- Instituto Superior de Agronomia
- Leibniz
- Max-Planck-Institute for Biological Cybernetics
- Nature Careers
- Stockholm University
- Technical University of Munich
- Technical University of Munich
- 1 more »
- « less
-
Field
-
molecular simulations, machine learning, statistical physics, multiscale modeling, and uncertainty quantification. The position is offered in the context of the EU funded project, aiming to develop a novel
-
Engineering, Mathematics, Statistics, or related fields. • Strong programming skills in Python, Java, C++, etc. • A solid foundation in generative AI, machine learning, and related areas. • An Interest in eye
-
or higher. You will be responsible for performing statistical analyzes regarding the accuracy of the AI algorithms compared to registered cancer diagnoses and compared with the radiologists
-
leverage computational methods, statistical models, and machine learning to dissect and interpret vast datasets to uncover novel insights that can lead to improved treatment strategies. Key Responsibilities
-
, Biotechnology or equivalent, obtanied in up to 5 years.- Independent, proactive researcher who should work well in a team.- Experience in plant biochemistry and plant molecular biology, as well as in statistical
-
areas: Forestry and Agriculture/Earth and Environmental Sciences Skills: - Training and knowledge in Remote Sensing, Spatial Analysis, and Statistical Analysis; - Programming in Python, R, Google Earth
-
annotation, development and application of comparative genomic methods to discover differences in genes and gene expression, and the use of statistical approaches to link phenotypic to genomic changes. Our lab
-
science. Experience in collection and analysis of human sleep EEG data or simultaneous EEG-MRI data are required. Advanced signal processing, statistical and programming skills are strong assets. Fluency in
-
application of comparative genomic methods to discover differences in genes and gene expression, and the use of statistical approaches to link phenotypic to genomic changes. Our lab is part of TBG (https
-
, genomics)•Bioinformatics and statistical analysis•Interaction with multiple research groups•Publication and scientific communication of the resultsYour profile•PhD degree in biology, ecology, bioinformatics