PEPFAR Scholars

In collaboration with Data Collaboratives for Local Impact program (DCLI) and College of ICT, University of Dar es Salaam, dLab is offering up to 5 scholarships each year since 2018 for qualified individuals, applying for the newly established Master of Science in Data Science degree programme in the Department of Computer Science and Engineering at the University of Dar es Salaam.

The scholarship covers all tuition and fees for two years. The UDSM MSc. Data Science in collaboration with the Tanzania Data Lab (dLab) aims to develop practical skills in advanced data analytics, visualization and other areas of data science sub-disciplines which are in high demand. 

Scholarship award is subject to acceptance to the MSc in Data Science with UDSM CoICT, maintenance of good academic standing for the duration of the program, and an interest in contributing to saving lives and ending HIV/AIDS. If accepted, the applicant commits to participating in dLab activities and training throughout the program, and to at least 3 months of “in-resident” work at dLab in support of data science research and solutions related to health, gender equality and economic empowerment as contributors to ending the AIDS epidemic.


    Brenda W. Mtenga
    Brenda Walter Mtenga has expertise in economics and finance. Her research is on HIV drug adherence
      Cylirus Kaijage
      Cylirus has a BSc. In Applied Statistics
        Joseph Kwagilwa
        Joseph has a BSc. in Computer Science
          Saida Nyasasi
          Saida is a computer engineer. Her research is on assessing risk factors for invasive cervical cancer among women living with HIV/AIDS by using machine learning predictive techniques


            David Rugeihyamu
            David Rugeihyamu has expertise in telecommunication engineering. He is researching on using social media to provide HIV/AIDS information to people aged of 15-49 years old
              Meshack Mbeswa
              With knowledge in official statistics, Meshack's research is on prediction of HIV drug resistance using socio-cultural, economic, health and economic factors
                Mussa Josiah
                As an expert in informatics, Mussa's research is focused on the effect of developing a random forest model to predict the progression of HIV in antiretroviral initiating patients in Tanzania


                  Upendo Mchome
                  Upendo Mchome has a bachelor degree in Information System Management. Her research is on Antiretroviral Therapy dropout prediction model based on PLHIV-centric adherence predictors
                    Frida Fulgence
                    Frida Fulgence is an expert in IT and digital financial services. Her research is exploring the probabilistic graphical model for HIV prevalence prediction
                      Rodrick Kayombo
                      Rodrick Kayombo has experience in Computer Science, IT audit, and financial audit. Rodrick's research is looking into blockchain based framework for crowdsourcing medical data collection
                        Mwanahamisi Suleiman
                        Mwanahamisi Suleiman is a telecommunication engineer. Through her research, she is studying the prediction of viral suppression in Adolescents living with HIV/AIDS using non-virological and non-immunological features

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