Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- Umeå University
- Linköping University
- SciLifeLab
- KTH Royal Institute of Technology
- Lunds universitet
- Karlstad University
- Karolinska Institutet (KI)
- University of Lund
- Uppsala universitet
- Blekinge Institute of Technology
- Institutionen för biologi och miljövetenskap
- Luleå University of Technology
- Luleå tekniska universitet
- Swedish University of Agricultural Sciences
- The Royal Institute of Technology (KTH)
- University of Skövde
- Uppsala University
- 8 more »
- « less
-
Field
-
qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
-
. Contact information If you have any questions about the position, please contact: Patrice Pottier Phone: +46702976011 Email: [email protected] Webpage: patricepottierlab.com Åsa Arrhenius, Head
-
applications sent by email will not be considered. Contact details to references will be requested after the interview. We welcome your application no later than October 15, 2026. For questions, please contact
-
analyses. The postdoc will be hosted at TDB, co-supervised by both groups, and will work at the interface of scientific computing, machine learning and particle physics. Project description Searches for dark
-
/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability
-
electronically, in pdf or word format, in the application template. Research publications, e.g. monographs, which cannot be sent electronically should be sent in three sets by mail to the University Registrar
-
subject. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability
-
related subject. Proven experience with X-ray imaging techniques, e.g. µCT, nanoCT, TXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability to work both
-
regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
-
environment including several research groups with extensive experience in virology, biochemistry, structural biology, cellbiology and imaging. Both the Umeå Core facility for Electron Microscopy (http