Sort by
Refine Your Search
-
Listed
-
Employer
- Linköping University
- Lulea University of Technology
- SciLifeLab
- Chalmers University of Technology
- Umeå University
- Uppsala universitet
- Luleå University of Technology
- University of Borås
- KTH Royal Institute of Technology
- Karolinska Institutet
- Karolinska Institutet, doctoral positions
- Linnaeus University
- Mälardalen University
- Nature Careers
- University of Lund
- 5 more »
- « less
-
Field
-
application! We are looking for up to two PhD students in Generative AI and Machine Learning Your work assignments We are looking for up to two PhD students working on generative AI/machine learning, with
-
, computer science, computational biology and computational statistics. More information about us, please visit: Department of Mathematics . Project description We seek to recruit a PhD student for the following
-
conversational guides for enhancing visitors’ learning and experiences in public educational environments. The PhD student will focus on addressing the challenge of visual blindness in large language models (LLMs
-
relevant to both the healthcare sector and society at large. We are looking for a PhD student in Biomedical Engineering Sciences in the field of biological systems modeling and deep learning Your work
-
computational and data science capabilities in Swedish life sciences. DDLS is establishing a research school for 260 PhDs in academia and industry. The aim is to educate highly skilled and competent professionals
-
, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
-
for Computer Vision conducts research and education in machine learning for computer vision at the undergraduate, advanced, and PhD levels. CVL has been identified as an outstanding Swedish research environment
-
of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
-
machine learning, engineering, data sciences, applied mathematics, or another related field; or Have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including
-
particularly valuable. Documented experience with machine learning and biostatistics is also highly meritorious.You can find information about education at postgraduate level, eligibility requirements and