Senior data scientist position to help empower personalized cancer therapy

Senior data scientist

Job description

OncoImmunity is seeking to add to its growing team, a senior level data scientist motivated to apply their machine-learning skills in the fight against cancer. The candidate will develop novel algorithms to identify immunogenic mutations from cancer patients that will be used to design personalized cancer vaccines. The candidate should be experienced in applying machine-learning and statistical methods to the analysis of high-dimensional data, preferably biological data. Experience in the analysis and application of machine learning algorithms to NGS data in the field of cancer would also be advantageous.

Required experience

We are looking for applicants who have a PhD in one of the following disciplines; bioinformatics, statistics, computational biology, computer science, applied mathematics, in addition to several years experience at a senior level.

Important attributes:

  • Excellent communication skills, and capable of providing clear visualization of data and results.
  • Very experienced and a desire to be hands-on in computer programing with strong familiarity with languages, tech-stacks and libraries needed for statistical data analysis and machine-learning (preferably Python).
  • Self-driven scientist that will cultivate a passion to build innovative software solutions to benefit cancer patients, by empowering the prediction of groundbreaking immunotherapies.
  • Minimum 5 years experience after your PhD degree is preferred for this position.
  • A deep understanding of statistics is a major plus.
  • A deep understanding in the building of neural network based models is a major plus.
  • Very comfortable in manipulating and analyzing complex and high-dimensional data from varying sources.

Roles and responsibilities

  • Work on challenging fundamental data science problems in the field of cancer immunotherapy and cancer genomics.
  • Develop and follow best practices for both data analysis and commercial software development.
  • Write high quality efficient code that will contribute toward product development.
  • Prepare and author on white papers, scientific publications and patents.
  • Develop and apply innovative machine-learning methods to NGS data in the field of cancer immunotherapy.
  • Work on the formulation, implementation, testing and validation of your predictive models.
  • Apply great leadership and teamwork skills, working very closely in a diverse and multidisciplinary scientific team.

Om arbeidsgiveren

OncoImmunity is a machine-learning based company providing software to empower personalized cancer immunotherapy. We are adding to our growing team, 6 new developers with a passion to apply their computational skills to build an innovative software solution that will benefit cancer patients.
Our flagship product predicts, from next generation sequencing (NGS) data, targets specific to a patient’s tumor that can be used to design personalized cancer immunotherapies. We are a growing team from 8 different countries consisting of a diverse mix of data-scientists, bioinformaticians, immunologists, cancer researchers and software developers. The company is located in the dynamic Oslo Cancer Cluster , which is home to a synergistic ecosystem of organizations that include the Cancer Registry, the Institute for Medical Informatics and Pathology and a mix of exciting local and global biotech companies. We work in a collaborative, innovative and fun environment, committed to deliver powerful machine-learning solutions in the field of cancer immunotherapy. The OncoImmunity team is driven daily by its mission of being the worlds leading supplier of machine learning software to guide personalized cancer immunotherapy

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Ullernchausseen 64/66, 0379 Oslo
IT - programvare
IT utvikling / Utvikler (generell),
IT utvikling / Database


machine-learning, statistics, data-science, bioinformatics, genomics

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Trevor Clancy
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Ullernchausseen 64/66, 0379 Oslo

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FINN-kode 122996405
Sist endret 2. aug. 2018 23:34

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