Employment Opportunities

  • We are seeking to fill multiple pre- and one post-doctoral positions at the earliest possible date. You will join a multi-disciplinary team to contribute towards our long-term goal of advancing endoscopic sinus procedures by personalizing stratification, guiding and monitoring treatment, and rethinking instrumentation to improve patient outcomes. To this end, we perform synergistic research at the intersection of computer vision, machine learning and data science, robotics, and human-computer interaction to develop collaborative intelligent systems that accomplish those goals.

    This research is based in the Malone Center for Engineering in Healthcare (MCEH) and the Laboratory for Computational Sensing and Robotics (LCSR) at Johns Hopkins University. Depending on the position, you will be advised by a combination of Professors Gregory Hager, Russell Taylor, and Mathias Unberath in the Department of Computer Science, and you will collaborate closely with Dr. Masaru Ishii in the Department of Otolaryngology – Head and Neck Surgery.

    We are committed to identifying candidates who will contribute to the diversity and excellence of the academic community. More information on diversity and inclusion in the department is available at https://www.cs.jhu.edu/diversity/. We are also committed to providing a highly supportive and dynamic environment for junior investigators to grow and develop their future career. Ideally, you should have demonstrated experience (through coursework transcripts and/or peer-reviewed publications) in one or more of the following fields: Medical image analysis, image reconstruction and registration, 3D shape modeling, computer vision incl. machine learning, and human-computer or human-robot interaction. We are particularly looking for creativity, enthusiasm, good communication skills, and interest in growth opportunities as part of a multi-disciplinary team. By the start date, for pre- or post-doctoral positions you must have completed a Bachelor’s or PhD degree, respectively.

    If you are interested in joining us, please send an email to Professors Gregory Hager and Mathias Unberath  making sure to include [Application – MCEH/LCSR] in the subject line. Please include a brief cover letter highlighting your research experience and interests, a full curriculum vitae, and the names and contact information of two references. If applying to the postdoctoral position, please also supply reference to at least two recent publications, and if possible, a brief research statement.

    Review of applications will begin immediately and will continue until the positions are filled. The Johns Hopkins University is an Affirmative Action / Equal Opportunity Employer. There are no citizenship restrictions for this position.

  • If you love developing fundamental machine learning models and algorithms inspired by complex phenomena such as natural language, please consider joining Johns Hopkins University as an Assistant Research Professor of Computer Science. You would be affiliated with the Center for Language and Speech Processing (CLSP), one of the largest and most influential academic groups in NLP and speech.

    This is a great launching pad to start an academic career, or to move back into academia from industry. This opportunity is appropriate for individuals who are also considering postdoctoral, industrial, or tenure-track employment. It provides a competitive salary and an excellent platform for career advancement. Initially, you would be working closely with Jason Eisner and his excellent students, helping to advise and develop a range of ongoing research projects.

    Appointment renewal will be based on performance and funding availability. Currently funding is available for the first 3 years. There would be several paths for you to raise further funding if you wished to continue in the position. The university has instituted a non-tenure track career path for full-time research faculty culminating in the rank of (full) Research Professor.

    Qualifications:
    Desirable qualifications for this position:

    • D. in computer science or a closely related field
    • Background in ML, preferably structured prediction and/or reinforcement learning
    • Background in NLP, preferably with knowledge of linguistics or grammar formalisms
    • Some familiarity with programming language design, data structures / algorithms, or HCI
    • Strong writing skills, including mathematical exposition
    • Intellectual curiosity, scientific integrity, concern for experimental design
    • Management and mentoring skills

    Application Instructions:
    Applications may be submitted online through Interfolio by clicking here. Questions should be directed to jason@cs.jhu.edu . Start date of summer or fall 2021 (negotiable). Applications will be reviewed until the position is filled.

  • Applications are invited for a cybersecurity postdoctoral fellow to conduct research on vulnerability discovery, analysis, and patching in the System Security Lab lead by Dr. Cao (https://yinzhicao.org).  The System Security Lab has profound experience in Web Security and a track record in publishing academic papers in the top-four cybersecurity conference.

    Ideal applicants will have:

    • A Ph.D. in Computer Science, or related field • Strong programming skills in relevant languages and frameworks such as JavaScript and IBM WALA • Strong programming analysis skills, such as control and data flow analysis • Published papers in English • Excellent communication skills

    To apply, send yzcao (at) cs.jhu.edu a letter of interest and current CV. Please also arrange for two letters of recommendation to be sent to that address. Applications will be reviewed until the position is filled. Questions should be directed to yzcao (at) cs.jhu.edu.

    The Johns Hopkins University is an EEO/AA employer.

  • In 2013, the university announced the funding by alumnus Michael R. Bloomberg of 50 new Bloomberg Distinguished Professorships to anchor programs of cross-disciplinary collaboration across the university. Computer Science is pleased to be involved in several of these searches.

 

 

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