Jille van der Togt
Tell us a bit about yourself.
“Hey, I’m Jille. I’m a graduate student in Artificial Intelligence at the University of Amsterdam. I have worked at numerous healthcare-related companies during my studies. While working with one of the biggest hospitals in the Netherlands, I used AI to identify novel markers in hematology data for certain diseases. In my free time, I love to cook and bake, go hiking, take photos, and explore the Bay Area on my VanMoof.”
What was your motivation for applying to Internships in the Valley?
“I’ve always had the desire to work in the Bay Area. I tried applying to numerous companies independently but found it incredibly difficult to find a company that was willing to handle the visa process. My motivation for applying to Internships in the Valley was to overcome this hurdle. I am thankful for the program at Internships in the Valley for organizing the visa application and for guiding us for our transition to the US.”
What is your role at RTHM? Has your internship taught you any new hard or soft skills?
“I have been working as an AI scientist intern for RTHM and have already learned many new skills in my few months here. Firstly, recreating the way we store all our patient data has taught me a lot about data relationships and structure. Then, all this data has to be surfaced for the doctors and patients in a particular way, so I’m learning a lot about the best visualization practices. Finally, working in a startup with people working all across the US has shown me different ways of interacting with people, compared to only having in-person meetings.”
Tell us about your recent trip to New York City.
“In September I had the chance to take a short trip to New York, just in time to catch the first signs of autumn! This was my second time visiting the Big Apple. I spent my time taking strolls through Central Park, eating New York style pizza on 5th Avenue and admiring the Manhattan skyline from the Empire State Building and DUMBO.”
“My role at RTHM involves helping with data-related tasks and finding more efficient ways to treat patients through machine learning.
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