{"id":976,"date":"2015-10-06T14:54:34","date_gmt":"2015-10-06T05:54:34","guid":{"rendered":"http:\/\/www.cns.atr.jp\/dbi\/?page_id=976"},"modified":"2024-11-20T16:22:59","modified_gmt":"2024-11-20T07:22:59","slug":"open-positions","status":"publish","type":"page","link":"https:\/\/bicr.atr.jp\/dbi\/en\/open-positions\/","title":{"rendered":"Open Positions"},"content":{"rendered":"

Open researcher position at ATR Brain Labs., Kyoto, Japan<\/strong><\/p>\n

Advanced Telecommunications Research Institute International (ATR), Kyoto, Japan, has open researcher positions and invites applications from people with strong motivations and ambitions in the research project described below.<\/p>\n

We will study how to analyze multi-modal sensor measurements to create artificial intelligence that can understand semantically daily life situations based on machine learning.<\/p>\n

We seek a highly motivated research scientist or postdoctoral researcher to develop machine learning techniques for estimating brain states from non-invasive neuroimaging data (e.g. EEG and fMRI). Our current research interests include (but not limited to): <\/p>\n

(1) development of geometric deep learning methods for extracting common information shared by EEG and fMRI (Ju et al., ICLR2024) by utilizing simultaneous EEG-fMRI data of high quality that we possess (Kuroda et al., Imaging Neuroscience, 2024)<\/p>\n

(2) development of transfer learning methods for accommodating non-stationarity and individual differences in neuroimaging data (Kober et al., NeurIPS2022, ICASSP2022) <\/p>\n

Through such methodological research, our aim is to develop neuro-technology for monitoring brain states with EEG, which can be used in a real-life setting, by taking advantage of fMRI data. Once employed, candidates will have access to various multi-modal neuroimaging data recorded by experimental neuroscientists in our lab and also to our own Brain Machine Interface systems.<\/p>\n

[Keywords] Machine learning, multi-modal neuroimaging data, brain state estimation, neurotechnology, transfer learning<\/p>\n

We look forward to your applications and recommendations.<\/p>\n

Motoaki Kawanabe, Ph.D.
\nAdvanced Telecommunications Research Institute International (ATR), Kyoto, Japan<\/p>\n

 <\/p>\n

\u25a0 Requirements for Researchers<\/p>\n

Qualification:<\/p>\n

– Applicants must have a Ph.D. or expect to receive a Ph.D. before the date of employment<\/p>\n

– Applicants should possess a doctoral degree in machine learning, computer science, statistics or a related field of mathematical informatics.<\/p>\n

– Applicants should have interest in neuro-technology and\/or neuroscience<\/p>\n

– Having research experience in brain\/biomedical\/ambient data analysis will be advantageous, but not mandatory<\/p>\n

– Applicants should have programming skills and experience in machine learning methods (Python etc.)<\/p>\n

– Speaking Japanese is not mandatory, however, applicants must also have good communication skills and be able to cooperate with the relevant personnel within\/outside of the laboratory to fulfill the tasks.<\/p>\n

\u25a0 Number of openings<\/p>\n

Only a few positions available<\/p>\n

\u25a0 Employment conditions<\/p>\n

Position : Full-time Researcher<\/p>\n

Tenure\u00a0\u00a0 : Single year based contract, renewable based on evaluation<\/p>\n

Treatment: Based on individual performance<\/p>\n

Work Location: Advanced Telecommunications Research Institute International (ATR)<\/p>\n

2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan<\/p>\n

\u25a0 Application materials<\/p>\n

Please submit the following five materials to the contact address below, either in printed or electronic form:<\/p>\n

    \n
      \n
        \n
      1. CV<\/li>\n
      2. List of publications<\/li>\n
      3. Reprints (or PDF files) of 1-3 major publications<\/li>\n
      4. Essay (up to two pages in A4 or letter size) describing:<\/li>\n<\/ol>\n<\/ol>\n<\/ol>\n

        – Summary of your previous research and\/or development<\/p>\n

        – Interests for research<\/p>\n

        – Additional research skills not directly foreseeable from 1 or 2<\/p>\n

          \n
            \n
              \n
            1. Recommendation letters from more than or equal to two researchers<\/li>\n<\/ol>\n<\/ol>\n<\/ol>\n

              *If submitted in printed form, original documents will not be returned.<\/p>\n

              \u25a0 Judging system<\/p>\n

              After documentary examination, we ask for presentation and interview if needed<\/p>\n

              \u25a0 Starting date<\/p>\n

              Soon (negotiable)<\/p>\n

              \u25a0 Deadline for application<\/p>\n

              Opens until positions are filled.<\/p>\n

              \u25a0 Contact<\/p>\n

              \u3012619-0288\u00a0\u00a0 Department of Dynamic Brain Imaging<\/p>\n

              ATR Cognitive Mechanisms Laboratories\u00a0 (Application for Researcher Position)<\/p>\n

              2-2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan<\/p>\n

              (old) Email: dbi-cma at atr.jp\u3000 (Replace “at” with “@”)
              \n(new) Email: dbi-recruit at atr.jp\u3000 (Replace “at” with “@”)
              \nNote: We updated the email address. Please use the new one. <\/p>\n

              \u25a0 Use of personal data<\/p>\n

              All personal data received will be properly managed and only be used for the purpose of recruitment.<\/p>\n","protected":false},"excerpt":{"rendered":"

              Open researcher position at ATR Brain Labs., Kyoto, Japan Advanced Telecommunications Research Institute International (ATR), Kyoto, Japan, has open researcher positions and invites applications from people with strong motivations and ambitions in the research project described below. We will study how to analyze multi-modal sensor measurements to create artificial intelligence that can understand semantically daily life situations based on machine learning. We seek a highly motivated research scientist or postdoctoral researcher to develop machine learning techniques for estimating brain states from non-invasive neuroimaging data (e.g. EEG and fMRI). Our current research interests include (but not limited to): (1) development of geometric deep learning methods for extracting common information shared by […]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-976","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/pages\/976","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/comments?post=976"}],"version-history":[{"count":30,"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/pages\/976\/revisions"}],"predecessor-version":[{"id":2628,"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/pages\/976\/revisions\/2628"}],"wp:attachment":[{"href":"https:\/\/bicr.atr.jp\/dbi\/en\/wp-json\/wp\/v2\/media?parent=976"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}