Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Lunds universitet
- University of Lund
- KTH Royal Institute of Technology
- Chalmers tekniska högskola
- SciLifeLab
- Chalmers University of Technology
- Karolinska Institutet (KI)
- Umeå universitet stipendiemodul
- University of Gothenburg
- Uppsala universitet
- Örebro University
- Karolinska Institutet
- Linköping University
- Linköping university
- Lulea University of Technology
- Luleå tekniska universitet
- Mälardalen University
- Mälardalens universitet
- Nature Careers
- Stockholms universitet
- Sveriges Lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Umeå University
- Umeå universitet
- 14 more »
- « less
-
Field
-
quantitative methods, with a strong emphasis on GIS and spatial analysis. A central part of the work will be to trace the effectiveness of colonial health interventions across time and space, linking observed
-
sciences, bedrock geology, paleontology, physical geography, biodiversity and ecosystem science, remote sensing, Geographic Information Science (GIS), and computational science for health and environment
-
with Java or Python are additional merits. The successful candidate should be creative, have the ability to both co-operate and independently work with research questions. Proficiency in written and
-
stage. Strong programming skills (Python or R) and familiarity with high-performance computing Exceptional collaborative abilities Preferred qualifications A doctoral degree or an equivalent foreign
-
research in general are merits. The applicant must be proficient in the R statistical language, experience with Java or Python are additional merits. The successful candidate should be creative, have the
-
experience in handling large metagenome datasets (first author publication/s in the topic are required). Relevant experience in R and/or python programming (eg. pipeline development for metagenomic data
-
been completed earlier. Additional requirements Very good oral and written proficiency in English. Experience of programming, for example in Matlab, Python, Julia or R. Assessment criteria This is a
-
experience with Python and C++. Knowledge of motion planning under uncertainty is considered an additional merit. The applicant should have strong collaborative skills, communicate research effectively in both
-
to the subject area. The candidate’s doctoral degree should be primarily focused on computed tomography, image analysis or similar. Essential criteria are: Demonstrated experience in programming (e.g., Python, MATLAB
-
requirements: Very good oral and written proficiency in English. Ability to drive and independently progress the project Strong computational skills with considerable experience with programming with python