Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Lund
- Umeå University
- SciLifeLab
- Jönköping University
- Nature Careers
- Karlstad University
- Swedish University of Agricultural Sciences
- Chalmers University of Technology
- Karolinska Institutet (KI)
- Lunds universitet
- Academic Europe
- European Magnetism Association EMA
- Karolinska Institutet, doctoral positions
- Lund University
- The Faculty of Education and Society
- Umeå universitet
- Uppsala universitet
- 7 more »
- « less
-
Field
-
, lineage-tracing, and computational approaches to address clinically relevant questions in cancer and drug development. Our work is carried out in close collaboration with national and international partners
-
creating inclusive environments. Flexible and Supportive: Tailored training and career development designed to balance professional growth with personal commitments. State-ot-the-art Research: Engage in
-
equality and diversity as a strength and an asset. Your team, work duties and areas of responsibility The MAX IV Scientific Data group develops and supports software projects for data acquisition and
-
promotes learning and development for all employees. We are also committed to building a safe and positive environment for all employees through mutual respect and tolerance. Work duties and responsibilities
-
problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical
-
Associate Professor Stefania Giacomello. Examples of postdoctoral activities: Lead and develop independent research projects in line with the group’s focus Design, conduct and interpret computational analyses
-
biology, analytical chemistry, evolution, and data science. The workplace offers access to state-of-the-art core facilities for advanced microscopy and cytometry, cell and molecular biology, extracellular
-
backgrounds and perspectives lay the foundation for learning, creativity and development. We welcome people with different backgrounds and experiences to apply for the current employment. We kindly decline
-
generation, and explainability Evaluation methodologies for knowledge-intensive AI systems The project will be driven by real-world domain applications in materials, casting, and manufacturing, developed in
-
–environment systems. A central component of the project is the development of next-generation process-based eco-epidemiological models that explicitly integrate environmental variability, ecological