Thanks for the post, Henrik! As a side note, I was at SciPy Japan recently looking for skimage users — and potential contributors! =) I didn't see anyone from RIKEN, at least to my knowledge. I highly recommend that you attend next year! I intend to be there again. I'm in Australia so the time zone is really well aligned for collaborating with Japan. If you have any issues with skimage or want to make any contributions or improvements, please get in touch! I notice that you listed registration as one of the methods you are working with, and was hoping you could have a look at https://github.com/scikit-image/scikit-image/pull/3544 and how it would fit your needs. Registration and stitching is something that I want to develop in skimage in the coming months. Juan. On Wed, 5 Jun 2019, at 3:06 PM, Image Analysis wrote:
Dear all,
We have an opening for a post-doc in biomedical analysis. We highly support and encourage the usage of Python (and of course scikit-image). We are looking forward to hearing from you.
Best,
Henrik
Details:
The Brain Image Analysis Unit at the Center for Brain Science (CBS), RIKEN, Japan, seeks highly motivated individuals who will contribute to the development and implementation of image processing and image analysis techniques with a focus on brain image data.
The work will be done in a highly interdisciplinary research group consisting of scientists from the neural-scientific and medical research fields. The Brain Image Analysis Unit integrates deep learning techniques into new algorithms to improve state-of-the-art processing and analysis of brain imaging data. Emphasis is placed on developing methods for image registration, image stitching, tracking of neurons and axon fiber bundles, detection, and segmentation of structures and denoising, enhancement, and visualization of images.
CBS website: https://cbs.riken.jp/en/faculty/bia/ Lab website: http://bia.riken.jp/
About the unit and the project
The Brain Image Analysis Unit develops new algorithms for the processing and analysis of multi-modal brain imaging data such as two-photon, bright-field microscopy images, and MRI. We are in close collaboration with scientists from the neural-scientific and medical research fields. As a member of the Brain/MINDS project, the unit analyzes image data of the brain of the common marmoset monkey to help better understand the structure and function of the primate brain.
Artificial intelligence plays an important role in contemporary image analysis. In particular, machine learning techniques such as deep learning are indispensable for the automated analysis of large image data-sets. The Brain Image Analysis Unit contributes to this exciting new field by integrating deep learning techniques into new algorithms to improve state-of-the-art processing and analysis of brain imaging data. Emphasis is placed on developing methods for image registration, image stitching, tracking of neurons and axon fiber bundles, detection, and segmentation of structures and denoising, enhancement, and visualization of images.
Job description
The selected candidate will join the interdisciplinary Brain/MINDS project, and as a member of the unit will contribute to the development and implementation of image processing and image analysis techniques with a focus on (marmoset) brain image data. The work will be done in a highly interdisciplinary research group consisting of scientists from the neural-scientific and medical research fields. The emphasis is on developing cutting-edge technologies that improve current state-of-the-art and publishing high impact work in top-tier journals in order to build a substantial resume and strong international collaborations.
Experiences in biomedical image analysis is an advantage but not a requirement. This job may be a great opportunity to apply knowledge and expertise from the computer vision and/or image processing field to new problems in the biomedical field.
Location
Wako-City (Kanto district, 2-1 Hirosawa, Wako, Saitama 351-0198). RIKEN is located in very close proximity to the northern part of Tokyo. http://www.riken.jp/en/access/wako-map/.
The RIKEN campus is quite large and offers cafeterias, coffee shops, and a convenient store. From the nearest train station, it is only a 12 min train ride to the Ikebukuro-Station (Tokyo). The Ikebukuro-Station is a hub which connects many famous places in Tokyo, including Shinjuku (9 min train ride), Shibuya (18 min train ride) or Akihabara (19 min train ride). Many people prefer to avoid crowded streets and trains in their daily life and are living in close proximity to RIKEN. However, those who prefer living close to the nightlife and entertainment spots in Tokyo benefit from commuting out of the city in the morning, and returning in the evening (significantly less crowded than the other way around).
Qualifications
The candidate should have or be expecting to receive a Ph.D., by the time of employment, in related fields and have relevant research skills and experience in developing algorithms for the analysis/processing of biological/medical/neural images, computer vision, machine learning, deep learning, optimization, simulation, or similar fields, demonstrated by high-quality publications good English communication skills proficiency in a programming language (such as C++/Python/JS) good communication skills and ability to cooperate
Application & Employment
Start: October, 2019 (negotiable). For further details, please refer to the job posting URL https://cbs.riken.jp/en/careers/20190530_w19047_bia_r.html _______________________________________________ scikit-image mailing list -- scikit-image@python.org To unsubscribe send an email to scikit-image-leave@python.org