Machine Learning Engineer

Job Posting Number: 18229

Information Technology
New York, NY
February 7, 2018
Company Overview:

At Memorial Sloan Kettering (MSK), we’re not only changing the way we treat cancer, but also the way the world thinks about it. By working together and pushing forward with innovation and discovery, we’re driving excellence and improving outcomes.

For the 28th year, MSK has been named a top hospital for cancer by U.S. News & World Report. We are proud to be on Becker’s Healthcare list as one of the 150 Great Places to Work in Healthcare in 2018, as well as one of Glassdoor’s Employees’ Choice Best Place to Work for 2018. We’re treating cancer, one patient at a time. Join us and make a difference every day.

Job Details:

MSK is seeking a Machine Learning Engineer to join Dr. Thomas Fuchs’ new Computational Pathology team. As a member of our Computational Pathology team you will work to improve clinical practice in pathology by developing intelligent decision-support systems that lead to more-objective and reproducible results. The overarching goal is to lead the way in transforming pathology from a qualitative to a quantitative science. This is the perfect position for someone looking for both a challenging and rewarding career in machine learning.

Under supervision of the group leader, you will provide support to research projects at the Center by designing, developing, and implementing software tools for processing and analyzing multi modality data in pathology.

You Will:

  • Be a part of large machine learning projects and deep learning projects;
  • Work and collaborate with a top-notch team of machine learning experts, software engineers and medical doctors to build a new generation of artificial intelligence;
  • Conduct and support research and publications in machine learning and medicine;
  • Lead software engineers and junior researchers.

You Are:

  • Capable of building strong customer relationships and delivering customer-centric solutions
  • A good decision-maker, with proven success at making timely decisions that keep the organization moving forward
  • Able to work effectively in an environment notable for complex, sometimes contradictory information
  • Consistently achieving results, even under tough circumstances
  • Adept at planning and prioritizing work to meet commitments aligned with organizational
  • Adept at building partnerships and working collaboratively with others to meet shared objectives and goals
  • An effective communicator, capable of determining how best to reach different audiences and executing communications based on that understanding
  • Resilient in recovering from setbacks and skilled at finding detours around obstacles
  • Able to operate effectively, even when things are not clear or the way forward is not obvious
  • Adept at learning quickly, applying insights from past efforts to new situations

You Need:

  • PhD degree in Computer Science with an emphasis on machine learning or computer vision;
  • Cross-disciplinary and strong analytic skills;
  • Experience in building complex systems.

Desired Skills:

  • Experience in machine learning or computer vision;
  • Experience in developing biomedical applications;
  • Experience in high performance computing.

Our affiliated departments and centers:

http://thomasfuchslab.org/

https://www.mskcc.org/research-areas/labs/thomas-fuchs

http://gradschool.weill.cornell.edu/faculty/thomas-fuchs

https://www.mskcc.org/departments/pathology/warren-alpert-center-digital-and-computational-pathology

https://www.mskcc.org/departments/pathology

https://www.mskcc.org/departments/medical-physics

#LI-FA1

MSK is an equal opportunity and affirmative action employer committed to diversity and inclusion in all aspects of recruiting and employment. All qualified individuals are encouraged to apply and will receive consideration without regard to race, color, gender, gender identity or expression, sexual orientation, national origin, age, religion, creed, disability, veteran status or any other factor which cannot lawfully be used as a basis for an employment decision.

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