Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Uppsala universitet
- Swedish University of Agricultural Sciences
- Sveriges Lantbruksuniversitet
- Linköping University
- Mälardalen University
- Umeå University
- Chalmers tekniska högskola
- Luleå University of Technology
- Chalmers University of Technology
- Institutionen för biomedicinsk vetenskap
- Jönköping University
- Karolinska Institutet, doctoral positions
- Linköpings universitet
- Luleå tekniska universitet
- Lunds universitet
- Mälardalens universitet
- Nature Careers
- School of Business, Society and Engineering
- SciLifeLab
- Swedish University of Agricultural Sciences (SLU)
- Umeå universitet
- 11 more »
- « less
-
Field
-
Python for scripting and data analysis, metabolite ID via MS/MS and annotation (e.g. SIRIUS, HMDB, authentic libraries etc.), statistical uni- and multivariate analysis, data visualization (PCA score
-
. The required expertise includes raw UPLC-MS-collected data preprocessing with XCMS, MZmine or MSDIAL, normalization procedures, proficiency in R and/or Python for scripting and data analysis, metabolite ID via
-
of energy-aware planning and scheduling in manufacturing, -experience in programming (Python, C/C++, Java, etc.) and implementing intelligent automation, -previous participation in EU or international
-
system modelling. Solid knowledge in mathematics, physics, thermodynamics, energy technology, optimization, and programming for system modelling, with experience in tools such as Matlab, or Python
-
knowledge in programming (preferably in Python), personal characteristics, such as a creativity, thoroughness, and/or a structured approach to problem-solving are essential. Additional qualifications
-
such as Matlab, or Python. Excellent command of spoken and written English. Additional qualifications Experience with modelling, simulation, and optimization of energy systems. Experience in thermodynamic
-
and problem-solving skills are important, and previous experience or interest in coding (for example in R or Python) would be a clear advantage since the project involves handling and interpreting
-
molecular simulations. Previous hands-on experience in more than one of the following methods is considered an advantage: molecular simulations, Python programming, machine learning, or quantitative analysis
-
for candidates who have: Strong programming skills, particularly in Python Solid analytical and mathematical abilities Experience with machine learning Strong communication skills and proficiency in English The
-
have some experience with scientific programming, in particular in Python, PyTorch or similar, in particular with respect to advanced data analysis or modelling operations. PhD students at the department