Research Associate/Research Fellow (Data Scientist), Opportunity At Kent Ridge Campus, Singapore.

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Exploreture
  • Post Date: December 9, 2022
  • Applications 0
  • Views 133
Job Overview

Research Associate/Research Fellow (Data Scientist)

Job Description

 

The Department of Family Medicine (DFM) at NUHS was established in 2017 with the aim of supporting the Division of Family Medicine within the Yon Loo Lin School of Medicine of the National University of Singapore (NUS). DFM is composed of a multidisciplinary team of clinicians, researcher, medical educators, and administrators. DFM provides an exciting and dynamic place in which people of diverse backgrounds collaborate towards the common goals of achieving achieve excellence in Family Medicine education, research and practice.

As part of our efforts to significantly increase our research capacity, we are looking to appoint a highly motivated and skilled Research Fellow to lead the data science components of our research programmes (Research Associates with outstanding merit will be also considered). The vacancy provides an exciting opportunity to make a significant contribution to our research programmes for improving the lives of people receiving primary care. Our research spans across a wide range of areas relevant chronic diseases, including mental health, cancer care and multimorbidity; healthy longevity; family orientation; and quality of care, including continuity and coordination. It will offer opportunities of continued interaction with fellow data scientists at the NUS Department of Medical Bioinformatics.

 

 

The Research Fellow/Research Associate will have the following duties:

 

 

  • Acquisition, management and curation of clinical and research data within the NUHS environment according to the relevant ethical and security standards
  • Development of new concepts and algorithms in data science, machine learning, and artificial intelligence
  • Contribution to data analysis, reporting and publication of ongoing and new projects using state-of-the-art methods as appropriate to the data and study design.
  • Contribution to the preparation of research studies, grant proposals, ethics applications, manuscripts, and oral presentations as led by other team members
  • Contribution to the management of research activities including team coordination, mentoring/training of researchers and clinicians in data science and statistics, conducting research workshops and seminars

 

 

Job Requirements

 

  • Oversight and coordination of data science and biostatistics support staff, and potentially of students
  • Up-to-date knowledge of current and emerging trends in data science
  • Membership of the DFM research committee

The position is full-time for 1 year in the first instance, depending on project commitments and candidate’s career objectives.

The application should include a CV and a cover letter that describes the applicant’s specific interest in joining the Dept of Family Medicine. Only shortlisted candidates will be contacted. Salary will be matched according to the candidate’s qualifications and experience.

 

 

Qualifications

 

  • A background in data science with a Master’s or PhD degree in Data Science or a closely related field
  • Excellent understanding and experience of data science, machine learning and their applications across multiple subject domains as well as appropriate knowledge of related data science topics, including:
    • Processing and analyzing large datasets
    • Data wrangling & data visualization
    • Big Data analysis
    • Machine learning
  • Proficiency in JavaScript, Python, or other relevant programming languages
  • Proficiency in the use of data analysis environments (R, Matlab)
  • Excellent organisation, coordination, and problem-solving skills
  • Excellent time management skills and ability to prioritise projects with focus on quality and timely delivery of work
  • Excellent interpersonal and communication skills; team spirit

 

 

 

 

 

 

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Job Detail
  • Offered SalaryNot Specified
  • Career LevelNot Specified
  • ExperienceNot Specified
  • GenderBoth
  • INDUSTRYEducation
  • QualificationDoctorate Degree (Ph.D.)
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