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
- Nature Careers
- Technical University of Munich
- Technical University of Munich
- The Department of Pharmacology & Toxicology at Charles University, Faculty of Pharmacy in Hradec Kralove, Czech Republic
- Vanderbilt University
- 1 more »
- « less
-
Field
-
The Department of Pharmacology & Toxicology at Charles University, Faculty of Pharmacy in Hradec Kralove, Czech Republic | Czech Republic | 8 days ago
/confocalmicroscopy, live cell imaging, animal and human models).• Strong background in statistical analysis methods.Position Details and Benefits:• Duration: 1-3 years (start date negotiable, Summer/Fall 2024
-
applied to forest ecology or ecosystem process studies, statistical and visualization skills, and integration of multiple datasets.--Strong oral and written communication skills including demonstrated
-
, and executing laboratory work, data analysis, supervision of students, statistical analysis, and writing scientific publications. Entry requirements The candidate must hold a Ph.D. equivalent to a
-
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
-
, 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
-
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
-
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
-
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