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Application for Research Positions in Our Lab

Submit your application package via email to: 

Email: applications@vision.is.tohoku.ac.jp

Professor Takayuki Okatani,
Computer Vision and Image Analysis Lab.,
Graduate School of Information Sciences,
Tohoku University, Sendai, Miyagi, 980-8579, Japan.

Format of the subject of the email: Application to Position_name, Applicant_name_surname where Position_name can be one of the following;

  • Research Assistant Professorship (currently no open position)
  • Postdoctoral Research Positions
  • Ph.D.
  • M.Sc.
  • Summer Internship
  • Exchange Studentship
  • Undergraduate Research Studentship

Applications to Postdoctoral Research Positions:

Application documents: Please provide a copy of the following documents in PDF format, in a compressed file (zip, tar or rar) of a folder. Please rename the compressed file using Postdoc:

  1. Cover Letter.
  2. Research proposal.
  3. Curriculum Vitae (CV); summarizing education background, research and teaching experience.
    • Education Background; including links to copies of your undergraduate, MSc. and PhD theses,
    • Research Experience: A brief summary of completed and ongoing research projects.
      • Links to publications and code developed in these projects, and
      • Links to project webpages, if available.
    • Teaching Experience:
      •  A list of students you have supervised at the undergraduate and graduate levels along with links to their theses and research reports.
    • Contact details of at least one reference.
  4. Publication records:
    • A list of publications.
    • Links to reprints of at least three major publications:
      • Up to three reprints of journal articles and three reprints of conference articles in a field related to the position being applied for.

Position requirements: Research experience and interest in at least one of the following fields:

a. Information Sciences: Computer vision (priority), pattern recognition (priority), machine learning (priority), image and signal processing (priority), information theory, control theory, theoretical computer science, parallel and distributed computing.
 
b. Applied Mathematics: Optimization theory (priority), statistical data analysis (priority), stochastic analysis, probability and statistics, geometry and topology, numerical analysis.
 
c. Neuroscience: Computational and mathematical neuroscience (priority), cognitive neuroscience, neuroimaging, neuroinformatics, neurophysics, neuropsychology, systems neurosciences;

  • Background in biological and computational vision, decision making, perception, memory, and motion.
  • Hands-on experience in analysis of ECoG, fMRI and EEG data.

Applications to Ph.D. Positions:

Application documents: Please provide a copy of the following documents in PDF format, in a compressed file (zip, tar or rar) of a folder. Please rename the compressed file using PhD:

  1. Cover Letter.
  2. Research proposal.
  3. Curriculum Vitae (CV); summarizing education background, research and teaching experience.
    • Education Background; including links to copies of your undergraduate, and MSc. theses,
    • Research Experience: A brief summary of completed and ongoing research projects.
      • Links to publications and code developed in these projects, and
      • Links to project webpages, if available.
    • Contact details of at least one reference.
  4. Publication records:
    • A list of publications.
    • Links to reprints of at least one major publication.

Position requirements: Research experience and interest in at least one of the following fields:

a.     Information Sciences: Computer vision, pattern recognition, machine learning, image and signal processing, information theory, algorithms, data structures, programming languages, parallel and distributed computing;

  • Hands-on experience in programming using C/C++, Python, Matlab and script languages for  GPU and CPU clusters/grid.
  • Hands-on experience in employment and development of computer vision, pattern recognition and machine learning methods of 2D/3D images, for object recognition/detection, segmentation, scene and video analysis.
  • Experience in employment of deep learning methods, such as Convolutional Neural Networks, Auto-encoders, and Recurrent Neural Networks.

b.    Applied Mathematics: Optimization theory, probability and statistics, functional and real analysis, linear algebra, discrete mathematics, numerical analysis, statistical data analysis.

c.   Neuroscience: Computational and mathematical neuroscience, cognitive neuroscience, neuroimaging, neuroinformatics, neurophysics, neuropsychology, systems neurosciences;

  • Background in biological and computational vision, decision making, perception, memory, and motion.
  • Hands-on experience in analysis of ECoG, fMRI and EEG data.

Applications to M.Sc. Positions:

Application documents: Please provide a copy of the following documents in PDF format, in a compressed file (zip, tar or rar) of a folder. Please rename the compressed file using MSc: 

  1. Cover Letter.
  2. Research proposal.
  3. Curriculum Vitae (CV); summarizing education background, research and teaching experience.
    • Education Background; including links to copies of your undergraduate theses/reports,
    • Research Experience: A brief summary of completed and ongoing research projects.
      • Links to publications and code developed in these projects, and
      • Links to project webpages, if available.
      • Contact details of at least one reference.
  4. Publication records:
    • A list of publications.

Position requirements: Research experience and interest in at least one of the following fields:

a.     Information Sciences: Computer vision, pattern recognition, machine learning, image and signal processing, information theory, algorithms, data structures, programming languages, parallel and distributed computing;

  • Hands-on experience in programming using C/C++, Python, Matlab and script languages for  GPU and CPU clusters/grid.
  • Hands-on experience in employment and development of computer vision, pattern recognition and machine learning methods of 2D/3D images, for object recognition/detection, segmentation, scene and video analysis.
  • Experience in employment of deep learning methods, such as Convolutional Neural Networks, Auto-encoders, and Recurrent Neural Networks.

b.    Applied Mathematics: Optimization theory, probability and statistics, functional and real analysis, linear algebra, discrete mathematics, numerical analysis, statistical data analysis.

c.   Neuroscience: Computational and mathematical neuroscience, cognitive neuroscience, neuroimaging, neuroinformatics, neurophysics, neuropsychology, systems neurosciences;

  • Background in biological and computational vision, decision making, perception, memory, and motion.
  • Hands-on experience in analysis of ECoG, fMRI and EEG data.

Applications to Positions for Summer Internship, Exchange Studentship and Undergraduate Research Studentship:

Applicants should contact the faculty members of the lab. at least 6 month prior to the considered position start date. Since these positions are short-term/mid-term positions, applications will be evaluated according to their background and interest in the appropriate research projects. Therefore, sufficient knowledge of elementary topics is required to participate in the related research projects.

Application documents: Please provide a copy of the following documents in PDF format, in a compressed file (zip, tar or rar) of a folder. Please rename the compressed file using SumInt, Exchange and Undergrad according to the appropriate position:

  1. Cover Letter.
  2. Research proposal.
  3. Curriculum Vitae (CV); summarizing education background, research and teaching experience.
    • Education Background; including links to copies of your undergraduate theses/reports,
    • Research Experience: A brief summary of completed and ongoing research projects.
      • Links to publications and code developed in these projects, and
      • Links to project webpages, if available.
    • Contact details of at least one reference.
  4. Publication records:
    • A list of publications.
    • Links to reprints of at least one major publication.

Position requirements: Research experience and interest in at least one of the following fields:

a. Information Sciences: Computer vision, pattern recognition, machine learning, image and signal processing, information theory, algorithms, data structures, programming languages, parallel and distributed computing;

  • Hands-on experience in programming using C/C++, Python, Matlab and script languages for  GPU and CPU clusters/grid.
  • Hands-on experience in employment and development of computer vision, pattern recognition and machine learning methods of 2D/3D images, for object recognition/detection, segmentation, scene and video analysis.
  • Experience in employment of deep learning methods, such as Convolutional Neural Networks, Auto-encoders, and Recurrent Neural Networks.

b. Applied Mathematics: Optimization theory, probability and statistics, functional and real analysis, linear algebra, discrete mathematics, numerical analysis, statistical data analysis.

c. Neuroscience: Computational and mathematical neuroscience, cognitive neuroscience, neuroimaging, neuroinformatics, neurophysics, neuropsychology, systems neurosciences;

  • Background in biological and computational vision, decision making, perception, memory, and motion.
  • Hands-on experience in analysis of ECoG, fMRI and EEG data.