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Winnie Mkandawire Graduates with a Distinction

Winnie Wezi Mkandawirejoined Malawi-Liverpool-Wellcome Trust as a CORE MLW-CoM Pre-Master intern with the Pathogen Biology Research Group in 2018. Under the supervision of Prof Dean Everett, and the mentorship of Dr. Anmol Kiran, Dr. Benjamin Kumwenda, Dr. Charlotte Van der Veer, and Dr. James Jafali, she was involved in two research projects that focused on the Genetic basis and temporal trends in antimicrobial resistance of two ESKAPE pathogens: Klebsiella pneumonia and Enterococcus faecium in Malawi.

Through these projects, she developed skills in the application of bioinformatics tools for characterizing pathogen antimicrobial resistance as well as skills in data analysis using python and statistical software such as Stata and R.

“I found the opportunity to network with senior researchers both locally and internationally which was an exceptional opportunity for horizontal exchange and gaining of experience and skills. This I regarded as a valuable aspect of my internship. This research training assisted me to be exposed, build confidence, gain practical experience and develop my research knowledge and skills in Bioinformatics,” Mkandawire recalled. 

It is from this experience where she got more interested to pursue graduate studies in Bioinformatics and its applications. In 2019, Winnie was awarded a prestigious Fulbright Scholarship to pursue Master’s in Bioinformatics and Computational Biology at Worcester Polytechnic Institute (WPI), USA, to which she graduated with a distinction, and implemented a project that illuminated the structural evolutionary conservation of functional regions of SARS-CoV-2 viral proteins. She has recently got admission into a PhD program in Basic and Biomedical Sciences – majoring in Bioinformatics with the University of Massachusetts Medical School (UMMS) under a competitive UMSS full scholarship. 

Winnie’s interest is in trans-disciplinary projects incorporating data analysis and visualization of genomic and epidemiological datasets, clinical machine learning for emerging infectious diseases, and mobile health with applications in outbreak prevention, risk prediction, and elucidation of mechanisms in biological systems.

We are proud of you, Winnie Mkandawire!