Research Staff Member


We are seeking Research Staff Members with proven publication records in one or more of our focus areas and with significant technical leadership potential. As part of the IBM Research team, you will conduct world-class research on innovative technologies and solutions and publish in top-tier conferences and journals. You will also have the opportunity to contribute to the commercialization of the resulting assets.

PhD candidates in fields such as Biology, Biochemistry, Computational Biology, Bioinformatics, Microbiology, Security, Computer Science (with a focus on data mining, machine learning, visual analytics) or related areas are encouraged to apply.
Desired Focus Areas of Technical and Professional Expertise
  • Security and digital rights management as well as emerging platforms (Spark, SQL/NoSQL, Blockchain), and/or,
  • Data management and/or machine learning algorithms and platforms to apply to business solutions, and/or,
  • Molecular biology, applied use of next generation sequencing data, as well as experience with high performance informatics and statistical methods (including programming skills in Java, Python, Perl, R, or equivalent languages).
You should be able to create innovative, original ideas, translate them into concepts, and execute on them in the context of our team. This includes, publishing papers, contributing to the patenting process and so forth. We also collaborate closely as a team, within our lab, our stakeholders in the company, and the external academic and technical community. Communication skills are essential to be successful.

  • 2 years experience in security, digital rights management and emerging security platforms (Spark, SQL/NoSQL, Blockchain)
  • 2 years experience with data management technology, machine learning algorithms and platforms to apply to business solutions
  • 2 years experience in molecular biology and use of next generation sequencing data as well as experience with high performance statistical computing

Group ID: IBM Research
Job Family: Not Applicable

Type: Full-Time

Experience: Mid-Senior Level

Category: Research

Reference ID: 77979BR

Date Posted: 01/08/2017