Research Assistant

3 weeks ago

Singapore National University of Singapore Full time
Other Responsibilities and DutiesJob Description

The National University of Singapore invites applications for Research Assistant role funded by Centre Grant Programme 'MOlecular Markers, MEchaNisms and their TherapeUtic Manipulation in CardioVascular Disease (MOMMENTUM-CVD)'> in Yong Loo Lin School of Medicine, Department of Medicine. Research will be pursued across the translational spectrum from molecule to man in the basic and applied (clinical) sciences to provide improved risk stratification, treatment selection and monitoring of response to therapy in CardioVascular Disease (CVD). Key to our research agenda is expanded interrogation of finely annotated cardiovascular clinical cohorts and biobanks acquired in the course of predecessor CGs together with prospective initiatives sparked from these background data sets.

Of the eight themes in MOMMENTUM-CVD, Research Assistant would be assisting with Theme 7: Health Services research and implementation of enhanced post-myocardial infarction management, and Theme 8: Cardioinformatics - analysis of complex data sets, implementing Machine Learning and/or Artificial Intelligence and publishing in scientific journals.

Appointments will be made on a yearlycontract basis with the possibility of extension.

Purpose of the post

The Research Assistant (RA) will be responsible to, and work closely with, the Principal Investigator and study team members to ensure the successful completion of the research deliverables on time. The RA's principal role is to apply Machine Learning and/or Artificial Intelligence such as pattern recognition, predictive modeling, classification/clustering etc, onto cardiology datasets (clinical & wet lab) and publish findings in NUS whitelisted scientific journals.

Main duties and responsibilities

The Research Assistant will liaise with clinical and basic scientists in MOMMENTUM-CVD to come up with Machine Learning and or Artificial Intelligence methodologies onto cardiology datasets clinical & wet lab and publish findings in NUS whitelisted scientific journals.

Main Responsibilities and Duties

  • Perform literature academic review on topics relating to machine learning, artificial intelligence, clinical and basic science data, relevant to existing projects in MOMMENTUM-CVD grant.
  • Collect, clean, review and manage datasets from research teams.
  • Working with research teams to design, develop machine learning AI algorithm models to meet research aims deliverables for each research projects.
  • Experiment, implement, simulation and analysis of these models involving appropriate and relevant metrics.
  • To train, refine, evaluate and cross validate these models to ensure accuracy, precision and integrity of analysis.

Other Responsibilities and Duties

  • To communicate and collaborate with other research entities and present findings to overseas/local conferences.
  • Any other duties relevant to research not mentioned above that are assigned by PI.
Qualifications
  1. Bachelor degree in any science technology field.
  2. Competent in at least 3 or programming languages such as R, Python, SQL, STAT, MatLAB. (competent in all would be advantageous)
  3. Competent in data visualization tools such as Tableau and matplotlib.
  4. Previous experiences managing and worked on research datasets in public hospitals or any other healthcare systems would be very advantageous.
  5. Able to work independently and in a team, have an investigative and collaborative nature with excellent interpersonal communication skills.
  6. Excellent analytical and problem solving skills.
  7. Good organization skills with ability to multi-task in fast-pace and dynamic environment.

...

Remuneration will be commensurate with the candidate's qualifications and experience. Informal enquiries are welcome and should be made to Teo Zhen Long, at /

Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of three (3) referees to this job portal.

We regret that only shortlisted candidates will be notified.

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