Intern – Clinical Biometrics (Biostatistics)

CytokineticsSouth San Francisco, CA
6d$22 - $28

About The Position

Cytokinetics is a specialty cardiovascular biopharmaceutical company, building on its over 25 years of pioneering scientific innovations in muscle biology, and advancing a pipeline of potential new medicines for patients suffering from diseases of cardiac muscle dysfunction. We are seeking a highly motivated Intern to join our Clinical Biometrics group at Cytokinetics. Job Description: The Biometrics internship is designed to give students a real data application of machine learning algorithms, so that to identify patterns from clinical trial data. Interns will review currently available machine learning algorithms that are implemented using R software. Additionally, they will utilize actual clinical data and explore if clinically meaningful patterns can be detected using the machine learning methodologies. The Intern will gain hands-on experience of statical methods applied to real data, draw conclusions and communicate their findings. Perform the exploratory analyses using machine learning methods Consult with clinical research on clinical interpretation of the results. Re-run the analysis with clinical research input Present the results to clinical research team To familiarize with the therapeutic disease area, of oHCM and nHCM To learn and understand current available machine learning methods

Requirements

  • The position requires a motivated individual with the ability to work independently and in a team environment.
  • Master’s or PhD students preferred, will consider students pursing BS in Biostatistics / Statistics
  • Experience with R Programming
  • Excellent communication skills and the ability to troubleshoot problems with team members

Responsibilities

  • Perform the exploratory analyses using machine learning methods
  • Consult with clinical research on clinical interpretation of the results.
  • Re-run the analysis with clinical research input
  • Present the results to clinical research team
  • To familiarize with the therapeutic disease area, of oHCM and nHCM
  • To learn and understand current available machine learning methods
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