Post-doc in Biomedical Image Analysis

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Post-doc in Biomedical Image Analysis

Organization: 
Riken Center for Brain Science
Country of Position: 
Japan
Contact Name: 
Henrik Skibbe
Subject Area: 
Signal Processing Theory and Methods
Machine Learning for Signal Processing
Bio Imaging and Signal Processing
Image, Video and Multidimensional Signal Processing
Start Date: 
December 01, 2020
Expiration Date: 
April 01, 2021
Position Description: 

Job offer: Post-doc in biomedical image analysis

We have an opening for a post-doc in biomedical image analysis. We are searching for highly motivated candidates who are interested in working with us. We develop and integrate deep learning techniques into new algorithms to improve state-of-the-art processing and analysis of biomedical imaging data. This includes image segmentation, classification, filtering, but also image registration.

Our website : http://bia.riken.jp/jobs.php%3Flang=en.html

Job description

The selected candidate will join the interdisciplinary Brain/MINDS project which aims at studying the neural networks controlling higher brain functions in the marmoset, to gain new insights into information processing and diseases of the human brain.
As a member of the project, the selected candidate will contribute to the development and implementation of image processing and image analysis techniques with a focus on (marmoset) brain image data. We are seeking candidates who enjoy developing deep learning algorithms for image segmentation, 3D image registration/reconstruction (stack alignment), or related applications.
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. Map: 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 sightseeing, 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 deep learning techniques for the analysis/processing of images, demonstrated by high-quality publications.
  • expertise in biological/medical/neural image processing, image registration, computer vision, machine learning, optimization, or similar fields, is an advantage.
  • good English communication skills
  • proficiency in a programming language (such as C++/Python/JS)
  • proficiency in tensorflow, pytorch or a similar DL library
  • good communication skills and ability to cooperate

Application & Employment

RIKEN employees enjoy the benefit of a generous vacation and leave package. An overview of benefits can be found here: working-at-riken. For application details, please refer to the official job posting URL: https://cbs.riken.jp/en/careers/20200520_w20016_bia_r.html.

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