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  • Lecture time: Thursday: 12:30:00 - 13:20:00 ET
  • Lab time: Tuesday: 11:30:00 - 13:20:00 ET
  • Domain: Pharmaceutical
  • Keywords: NLP, UI/UX
  • Tools: AWS, Dash, Python
  • Citizenship: Open to all students
Summary

Merck scientists currently summarize the analytical data generated for a stability study into an unstructured table. To remedy, an NLP model could be used to extract the table from the document and parse it into a structured form.

  • Lecture time: Monday: 11:30:00 - 12:20:00 ET
  • Lab time: Friday: 11:30:00 - 13:20:00 ET
  • Domain: Agriculture
  • Keywords: Agriculture, Agronomy, Climate Change, Clustering, Feature Engineering, Forecasting, Weather Data
  • Tools: Climate Modeling, Clustering Algorithms, Data Exploration, Data Integration, Python, Time Series Data Analysis, Weather Forecasting
  • Citizenship: Open to all students
Summary

Create a 2024 forecast in the style of The Farmer’s Almanac that estimates the likeliest analog years. Key data elements include rainfall, temperature, and other agronomic factors like planting/harvest dates. Create a digital means for interacting with the platform.

  • Lecture time: Thursday: 09:30:00 - 10:20:00 ET
  • Lab time: Tuesday: 09:30:00 - 11:20:00 ET
  • Domain: Automobile
  • Keywords: Anomaly Identification, Spatiotemporal Analysis, Vehicle Telematics Data
  • Tools: GeoPandas, Python
  • Citizenship: Open to all students
Summary

Create spatiotemporal metrics for vehicle delivery routes. These KPIs will be used to characterize and compare delivery routes, identify anomalies and quantify trade-offs between time and energy

Merck - Medical Affairs
Open for Registration
  • Lecture time: Monday: 09:30:00 - 10:20:00 ET
  • Lab time: Friday: 09:30:00 - 11:20:00 ET
  • Domain: Pharmaceutical
  • Keywords: Medical Affairs, Public Health
  • Tools: Jupyter Notebooks, Python, R, R Shiny
  • Citizenship: Open to all students
Summary

Merck in the UK is excited to work with a student team and use modern data science techniques to address rare disease and public health challenges.

  • Lecture time: Tuesday: 13:30:00 - 14:20:00 ET
  • Lab time: Thursday: 13:30:00 - 15:20:00 ET
  • Domain: Agriculture
  • Keywords: Agriculture, biology, Data Visualization, Genetics, Manufacturing, Optimization, Sustainability, Visualizations
  • Tools: Clustering Algorithms, Excel, Python, R, SQL, Statistics
  • Citizenship: Open to all students
Summary

Use data science to identify key factors affecting seed quality and germination with large historical datasets and statistical tools to impact business decisions. Factors include weather, field location, farming practices, harvest date, seed genetics/handling/age/shape and more.

Microsoft - Social Media Impact
Open for Registration
  • Lecture time: Tuesday: 15:30:00 - 16:20:00 ET
  • Lab time: Thursday: 15:30:00 - 17:20:00 ET
  • Domain: Game
  • Keywords: Analytics, Games, Video Games
  • Tools: Azure, Machine Learning, NLP, Python
  • Citizenship: Open to all students
Summary

Players interact with Minecraft not only through play but through conversation and content consumption on social medaia. Understanding the holistic relationship of players to Minecraft is key to developing an experience that players will enjoy.

  • Lecture time: Monday: 09:30:00 - 10:20:00 ET
  • Lab time: Friday: 09:30:00 - 11:20:00 ET
  • Domain: Aerospace
  • Keywords: Predictive Analysis
  • Tools: Python
  • Citizenship: U.S. Citizens Required
Summary

***US Citizens ONLY*** Use health sensor data sets to train predictive models to calculate RUL of key system components.

  • Lecture time: Monday: 11:30:00 - 12:20:00 ET
  • Lab time: Friday: 11:30:00 - 13:20:00 ET
  • Domain: Aerospace
  • Keywords: Business Intelligence, Machine Learning, NLP
  • Tools: Python
  • Citizenship: U.S. Citizens Required
Summary

***US Citizens ONLY*** Build new advanced analytics using publicly available data to gain insight into emerging companies, trends in industry, influential people, and important startup businesses.

Merck - Drug Interaction Prediction
Open for Registration
  • Lecture time: Friday: 09:30:00 - 10:20:00 ET
  • Lab time: Monday: 09:30:00 - 11:20:00 ET
  • Domain: Pharmaceutical
  • Keywords: Database, data mining, NLP
  • Tools: Graph Neural Network, Python, Pytorch
  • Citizenship: Open to all students
Summary

Drug-drug interactions (DDIs) occur when the effect of one drug is altered by another drug. It is important to predict DDIs to avoid adverse drug reactions and improve patient safety. This proposal is to improve DDI prediction through database construction and model development.

  • Lecture time: Tuesday: 15:30:00 - 16:20:00 ET
  • Lab time: Thursday: 15:30:00 - 17:20:00 ET
  • Domain: Pharmaceutical
  • Keywords: Assay Optimization, Chromatography, NLP
  • Tools: AWS, Confluence, JIRA, Python
  • Citizenship: Open to all students
Summary

Students will develop an NLP model to extract chromatographic data from published literature. These findings would be stored in a searchable database. Gives Merck scientists a database for chromatographic conditions which can be used for method development.