Sort by
Refine Your Search
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Umeå University
- University of Lund
- SciLifeLab
- Karolinska Institutet (KI)
- Lunds universitet
- Swedish University of Agricultural Sciences
- Lulea University of Technology
- Mälardalen University
- Linköping University
- Luleå tekniska universitet
- The Swedish University of Agricultural Sciences
- Umeå universitet stipendiemodul
- Uppsala universitet
- Blekinge Institute of Technology
- Luleå University of Technology
- Uppsala University
- Institutionen för biologi och miljövetenskap
- Jönköping University
- Karlstad University
- Linköping University (LiU)
- Sveriges Lantbruksuniversitet
- Umeå universitet
- University of Borås
- University of Skövde
- universitypositions
- 17 more »
- « less
-
Field
-
for parameter estimation, degradation prediction, and analysis of electrochemical and structural characterization data, including X-ray CT image reconstruction, segmentation and quantitative microstructure
-
or scale-up of algal cultures; biomass harvesting and characterization; trace-element analysis; geochemical or mineralogical methods; and statistical analysis of multivariate experimental data. Personal
-
. Contribute to optical instrumentation development, data analysis, and integration with complementary microscopy techniques. Investigate nanoparticle behaviour and interactions in complex environments and
-
/SEA), and programming or data analysis in Python, MATLAB, Julia or similar tools. Great emphasis will be placed on personal skills. Join us at KTH KTH shapes the future through education, research and
-
; Collect, manage, analyse, and interpret data using transparent and reproducible workflows; Conduct evidence synthesis, meta-analysis, comparative analyses, or environmental modelling; Comply with relevant
-
10 Jul 2026 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Chemistry » Other Engineering » Chemical engineering Engineering » Materials engineering Technology
-
regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
-
research experience in areas such as cybersecurity, AI-supported systems, data-driven security, or closely related fields; has experience in implementing, evaluating, or applying AI/ML-based methods
-
regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
-
strong scientific background with relevant expertise in cell and/or molecular biology. Interest in programming, computational biology and statistic towards high-throughput data analysis is considered a