Research Fellow (Post-Doctoral) – Data Science, Climate and Maternal Health

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Research Fellow (Post-Doctoral) - Data Science, Climate and Maternal Health

  • Post Date:May 4, 2022
  • Views 368
0 Applications
  • Career Level Other
    Qualification Degree
    Experience 3-5 Years
  • Industry Health Care
Job Description

Duty Station: Harare, Zimbabwe
Contract Duration: 4 years with a review after 6, 12, 24 and 30 months

About

CeSHHAR Zimbabwe is an organisation that specialises in population health research and programming, including on sexual and reproductive health and HIV / AIDS. CeSHHAR has an extensive national, regional, and international academic and community partnership network. CeSHHAR is a partner in the new US National Institute of Health (NIH) funded project, the HEAT Center. The HEAT Center is part of the broader NIH DS-I Africa program, which aims to advance the application of data science to key health challenges in Africa, as well as build data science capacity across the continent. CeSHHAR has a diverse range of funders with an annual budget of US$8 Million for the 2022 financial year. Its funders include the Wellcome Trust, the Bill and Melinda Gates Foundation, United States NIH, UK Medical Research Council, Templeton World Charity Foundation, USAID, Global Fund for AIDS TB and Malaria, UNICEF and UNFPA. We partner very closely with the Liverpool School of Tropical Medicine (UK), Zimbabwe’s Ministry of Health and Child Care and international and regional centres of research excellence to evaluate national programmes and determine the impact, uptake, and cost effectiveness of novel reproductive health interventions

The HEAT Center is focused on the interaction between environmental heat and health, with sub-foci on heat and maternal and neonatal health. Key challenges to be tackled include the integration of complex and diverse health data, with geospatial and climate data (eg. satellite imagery, climate model data), in order to advance understanding of the complex interactions between human health, socio-economic conditions (e.g. housing, access to services), and weather extremes such as heat waves. The available postdoctoral Research Fellow opportunity will be predominantly focused on advancing data science and machine learning methods within the HEAT Center project on Heat and Maternal and neonatal health. However, there is scope and expectation that engagement with a variety of data science projects within the HEAT Center would take place. CeSHHAR is seeking a suitably qualified and experienced individual to fill the above-mentioned position.

Job role

  • Working as part of a team, the Research Fellow will be responsible for developing analysis proposals, conducting data analysis (including of a large Individual Patient Data (IPD) database), data management and harmonization, presenting at scientific meetings, writing manuscripts overseeing study conduct, data analysis and publication of results;
  • It is expected that the Research Fellow will supervise PhD student(s).

Qualifications and experience

  • A PhD in (Bio)Statistics, computer science, or related fields;
  • Strong programming skills.
  • Demonstrable experience with Python (or R or STATA) data processing and numerical packages including NumPy, SciPy and Pandas;
  • Experience providing training in data science methods;
  • Experience working with large and complex datasets (eg remote sensing, health data, climate model data);
  • Experience working in a JupyterHub environment will be an added advantage;
  • Demonstrable experience with Python machine learning packages such as scikit-learn, and at least one of the deep learning packages / platforms such as Keras, PyTorch or TensorFlow;
  • Ability and experience working in an international multi-disciplinary team.

To apply

If you are interested in the above position, please email your CV and application cover letter addressed to the Human Resources Manager and send to [email protected] Indicate the position you are applying for in the subject line.

Only short-listed applicants will be contacted.

Deadline: 13 May 2022 (4.30pm)