Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Lunds universitet
- Umeå University
- Karolinska Institutet (KI)
- Swedish University of Agricultural Sciences
- Mälardalen University
- SciLifeLab
- Blekinge Institute of Technology
- Linköping University
- Lulea University of Technology
- Luleå University of Technology
- The Swedish University of Agricultural Sciences
- Umeå universitet stipendiemodul
- University of Lund
- Institutionen för biologi och miljövetenskap
- Karlstad University
- Uppsala universitet
- universitypositions
- 9 more »
- « less
-
Field
-
proteomics, advanced image analysis, and computational approaches to investigate molecular and cellular heterogeneity and to integrate spatial molecular information with histopathological and clinical data. We
-
industry. You will continuously characterise NC batches for a shared sample bank, build a reference database and use AI-supported data analysis to compare qualities and identify deviations. The work is
-
collection with informal caregivers, healthcare professionals and other stakeholders, register and retrieve data from REDCap. Analyse qualitative data using, for example, reflexive thematic analysis
-
simulation and AI-supported data analysis are central tools. The work is carried out at the Department of Fibre and Polymer Technology and in collaboration with FOI and industrial partners. Qualifications
-
data analysis and machine learning (e.g. XGBoost), including model interpretation techniques (e.g. SHAP). Very good oral and written proficiency in English. Excellent communication skills, ability
-
subject area. The department has education assignments in engineering programs and master's programs. More information is available on our website . (https://kemi.uu.se/angstrom/?languageId=1 ). Work duties The
-
. Contribute to optical instrumentation development, data analysis, and integration with complementary microscopy techniques. Investigate nanoparticle behaviour and interactions in complex environments and
-
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
-
Further details are provided by Gerold Jäger, [email protected] , 0046-90-7866141. More information about the Discrete Mathematic Group members can be found here: https://www.umu.se/en/research/groups
-
), statistical analysis of LHC data or beyond-the-Standard-Model phenomenology, is meriting. Experience with large-scale training on GPU and HPC systems, with design of experiments and active learning, with open