Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- Lunds universitet
- Uppsala universitet
- University of Lund
- Karolinska Institutet (KI)
- Umeå University
- KTH Royal Institute of Technology
- Umeå universitet
- KTH
- Karolinska Institutet
- Linköping University
- Linköpings universitet
- SLU
- SciLifeLab
- Sveriges Lantbruksuniversitet
- Swedish University of Agricultural Sciences
- chalmers tekniska högskola
- 7 more »
- « less
-
Field
-
engineering, precision agriculture, data science, machine learning, automated systems, or a closely related field Have experience working with ruminants Have experience in precision agriculture and/or precision
-
the last three years prior to the application deadline. Experience in some of the following areas is meritorious: AI and machine learning; convex analysis; functional analysis; mathematical statistics
-
/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
-
novel manufacturing techniques is the key to improved heat transfer mechanisms and more efficient use of energy. Approximately 25 colleagues work in the division, including 15 PhD students
-
, development of chemical process solutions for repurposing of electrodes, and integration of AI-based vision and active machine learning to optimize the efficiency of the process. Writing publications and
-
and free-energy calculations in explicit solvent. The postdoctoral researcher will employ machine-learning-accelerated methods throughout the workflow, contribute to the development of new computational
-
materials and technologies. Using advanced computational modeling and machine learning, we seek to elucidate the mechanisms governing the self-assembly of lignin in different solvents and the formation
-
software related to the medical field Experience of specific software and programming languages, specifically ones suitable for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and
-
fellow devotes most of their time to research. There is the possibility of teaching up to 20%. Requirements Requirements PhD degree in in machine learning, automatic control, system identification, signal
-
. Merits for this position: PhD acquired within three years of last application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context