Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- SciLifeLab
- University of Lund
- Lunds universitet
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Uppsala universitet
- Karolinska Institutet (KI)
- Chalmers tekniska högskola
- Umeå University
- Nature Careers
- Linköping University
- Mälardalen University
- Swedish University of Agricultural Sciences
- Jönköping University
- Luleå University of Technology
- Umeå universitet
- University of Gothenburg
- Kungliga Tekniska högskolan
- Mälardalens universitet
- Stockholms universitet
- University of Borås
- Chalmers Tekniska Högskola AB
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg
- Institutionen för biomedicinsk vetenskap
- Karlstad University
- Karolinska Institutet, doctoral positions
- Linköping university
- Linköpings universitet
- Lulea University of Technology
- Luleå tekniska universitet
- Lund University
- School of Business, Society and Engineering
- Sveriges Lantbruksuniversitet
- The University of Gothenburg
- Umeå universitet stipendiemodul
- 25 more »
- « less
-
Field
-
. Requirements A doctoral degree related to Data Science, involving applied work in machine learning Experience with common ML frameworks (e.g., Tensorflow, PyTorch) Expert knowledge of Python or C/C++ Experience
-
and methods used for analyzing transcriptomic and proteomic data Strong skills in working with large-scale datasets, including relevant programming languages (eg, Python and R) as well as visualization
-
and mathematical modeling skills (e.g MATLAB, Julia, Python, FORTRAN etc.). The candidate should be able to handle practical problems and design, build, and work with experimental rigs related
-
experience of solid-state batteries. Experience in materials characterization and associated techniques (SEM, XPS, X-ray tomography, etc.) Experience in analysis coding (Python or MATLAB). Consideration will
-
requires excellent study results at the master’s level, strong programming skills in Python, and experience with at least one of the popular deep learning libraries (PyTorch, TensorFlow, Keras, etc.). Good
-
., Computer Science, Cognitive Science, Human Computer Interaction, Human Robot Interaction or Artificial Intelligence. experience in programming, preferably Python. fluent in spoken and written English. It is
-
results, high proficiency in programming (preferably in Python), good communication skills with sufficient proficiency in oral and written English, personal characteristics such as a high level of
-
experience of application of artificial intelligence including machine learning and deep learning algorithms. Documented programming skills in Python, R, or MATLAB. Very good knowledge of English, spoken and
-
one or more of the following areas: Single-cell and spatial transcriptomic methods Scientific programming in Python and/or R Machine learning or deep learning frameworks (e.g., PyTorch, TensorFlow
-
competitive level Proficiency in a scripting language like R or Python, as well as ability to work efficiently in a Linux command-line environment and on high performance computer clusters Excellent