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Open Postdoctoral position, faculty mentor Haruka Itakura

Important Info

Faculty Sponsor (Last, First Name): 
Itakura, Haruka
Department Name: 
Dept. of Medicine Division of Oncology
Postdoc Appointment Term: 
1 year, renewable to multiple years upon annual review
Appointment Start Date: 
Immediately
How to Submit Application Materials: 

Email itakura@stanford.edu with application materials

The Itakura Lab has an immediate opening for a highly creative and motivated postdoctoral scholar to conduct applied research in the areas of machine learning, pattern/feature detection, and parallel computing with a focus on either computer vision/image processing and analysis or genomic/molecular data processing and analysis. The overall objective for the position is to develop and apply computational frameworks (software tools) for the integrative analysis of multi-omic biomedical data to accelerate discoveries in cancer diagnostics and therapeutics. Our group focuses on implementing machine learning frameworks and radiogenomic approaches on heterogeneous, multi-scale cancer data (e.g., clinical, imaging, histopathologic, genomic, transcriptomic, epigenomic, proteomic). Projects include prediction modeling of survival and treatment responses, biomarker (feature) discovery, cancer subtype discovery, and identification of new therapeutic targets. Guided by critical and relevant problems in oncology, these projects have the potential to lead to clinically actionable or translatable findings.
 
The successful candidate will join the Department of Medicine, Division of Oncology at Stanford University and work with a multi-disciplinary team of clinicians, computational biologists, and statisticians. Job description:

  • Build and implement algorithms in machine learning applied to either imaging data (computer vision) or genomic/molecular data (computational biology)
  • Develop software tools for integrative analysis of heterogeneous, multi-omic cancer data using machine learning
  • Publish and present research findings in journals and conferences
Required Qualifications: 
  • PhD (or MD/PhD) in Computer Science, Engineering, Informatics, Statistics, Applied Physics, or a related field with strong skills in data mining, machine learning, or statistics
  • Experience in modeling, integrative analyses, parallel computing, and/or software development desirable
  • Biomedical knowledge or research experience is not a requisite
  • Demonstrated ability to work independently, problem-solve, author manuscripts, strive for innovation, and be highly self-motivated
  • Strong interpersonal and communication skills, and ability to work as part of a multi-disciplinary team
  • Positive attitude
Required Application Materials: 

1. CV
2. Cover letter summarizing past relevant research experience, current interests, and career goals
3. Complete contact information for three references

 

Stanford is an equal opportunity employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other characteristic protected by law.