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University of Pennsylvania, Philadelphia, PA, USA

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"Computational Analyst (Biomedical Sciences)"

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Computational Analyst (Biomedical Sciences)

University Overview

The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn's distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America's Best Large Employers in 2023.

Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play.

The University offers a competitive benefits package that includes excellent healthcare and tuition benefits for employees and their families, generous retirement benefits, a wide variety of professional development opportunities, supportive work and family benefits, a wealth of health and wellness programs and resources, and much more.

Posted Job Title

Computational Analyst (Biomedical Sciences)

Job Description Summary

The Baslan Lab is looking for a computational analyst to join our multidisciplinary team of researchers. The experienced analyst is expected to engage in research, independently and in collaboration with members of the group, by analyzing multi-model datasets, including next generation sequencing data, and developing novel analytics, including machine learning approaches. Responsibilities of the position include but are not limited to: (1) processing and analyzing large genomic datasets using supervised and unsupervised learning methods & (2) developing novel algorithmic approaches to advance diagnostic, prognostic, and treatment strategies in cancer. In addition, the individual will be asked to develop computer programs for distribution to the research community as well as management of datasets, including sequencing data.

Job Description

Job Responsibilities

  • Develop novel algorithms to analyze next generation cancer sequencing datasets.
  • Apply machine learning tools to build classifiers and predictors of disease and therapy in cancer.
  • Establish & maintain working analytical pipelines for the analysis of large genomic datasets.
  • Develop data management solutions and analysis code (e.g. computer programs)
  • Other duties and responsibilities as assigned

Qualifications

  • Master of Science in mathematics, physics, computer science, or bioinformatics and 3 to 5 years of experience or equivalent combination of education and experience is required. Ph.D. preferred.
  • Experience and expertise in analyzing next generation sequencing data with publications in the field.
  • Experience in computer programming languages commonly used in biomedical research labs (R, Python, C+).
  • Experience in machine learning approaches (ex: NN, NMF, etc.)

This position is contingent upon grant funding.

Job Location - City, State

Philadelphia, Pennsylvania

Department / School

School of Veterinary Medicine

Pay Range

$66,000.00 - $82,000.00 Annual Rate

Salary offers are made based on the candidate's qualifications, experience, skills, and education as they directly relate to the requirements of the position, and in alignment with salary ranges based on external market data for the job's level. Internal organization and peer data at Penn are also considered.

Equal Opportunity Statement

The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state or local law.

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