Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- SciLifeLab
- University of Lund
- Lunds universitet
- Linköping University
- Umeå University
- Swedish University of Agricultural Sciences
- KTH Royal Institute of Technology
- Uppsala universitet
- Blekinge Institute of Technology
- Karolinska Institutet (KI)
- Nature Careers
- Umeå universitet
- Lulea University of Technology
- Mälardalen University
- Umeå universitet stipendiemodul
- Högskolan Väst
- Jönköping University
- KTH
- Karolinska Institutet, doctoral positions
- Luleå tekniska universitet
- Mid Sweden University
- University of Gothenburg
- Örebro University
- Faculty of Culture and Society
- Göteborgs Universitet
- IFM/Linköping University
- Institutionen för akvatiska resurser
- Institutionen för kemi och molekylärbiologi
- Kungliga Tekniska högskolan
- Linköpings universitet
- Lule university of technology
- Luleå university of technology
- Mittuniversitetet
- SciCross
- SciLifeLab / Uppsala University
- Sveriges Lantbruksuniversitet
- The Swedish University of Agricultural Sciences (SLU)
- Umeå Plant Science Center
- 29 more »
- « less
-
Field
-
and in cell culture. Proficiency in R and/or python. Practical experience in analytical methods including multiplex flow cytometry and cytokine assays, as well as associated data analysis. Practical
-
Familiarity with R, STATA, IBM SPSS Statistics, or Python What do we offer? A creative and inspiring environment with wide-ranging expertise and interests. Karolinska Institutet is one of the world's leading
-
. Expertise in any of the following can be an advantage, but none is obligatory: Reproducible data analysis in R/Python/Julia Cell wall biochemistry Plant in vitro culture work In situ microscopy and
-
of novel 2D materials (e.g., thin-film deposition by PVD and CVD). Proven programming skills (e.g., Python) for instrument control and data analysis. You are a highly motivated and independent researcher
-
for mass spectrometry data processing and data deposition. Knowledge in data analysis using open science programming languages (e.g. R and Python) is advantageous. About the employment This is a full-time
-
learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place
-
Python) and data analysis or machine learning applied to materials science Ability to work in interdisciplinary project or industrial experience About the employment The employment is a temporary position
-
. Expertise in any of the following can be an advantage, but none is obligatory: Reproducible data analysis in R/Python/Julia Cell wall biochemistry Plant in vitroculture work In situmicroscopy and
-
Python, and used to working with large datasets and reproducible analysis workflows. Has a demonstrated ability to initiate and drive own research ideas, preferably with experience from writing and
-
scans. Experience with age-depth modelling (c14 dates, stratigraphic correlation). Experience with Python or similar programming language. Documented very good oral and written proficiency in English