Support experimental validation of designed proteins through a cloud laboratory. Prepare and optimize sequences, submit tests for binding, expression, thermal stability, or enzyme activity, track experiment progress, and retrieve results through the API.

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• Submit designed proteins for binding tests
• Request expression, thermal stability, or enzyme activity tests
• Optimize sequences for solubility before experiments

Analyze time series, observations ordered over time, using aeon in Python. Build classification, prediction, and clustering workflows, detect unusual patterns or changes, and compare methods through an interface compatible with scikit-learn.

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• Classifying time series by their patterns
• Forecasting future values from past observations
• Detecting anomalies and change points

Create original generative art with p5.js, using code to produce patterns and motion. Receive a written artistic concept and an interactive HTML viewer with adjustable parameters, reproducible random variations, seed navigation, and PNG downloads.

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• Create art from particle motion and flow fields
• Explore patterns by adjusting sliders
• Reproduce a favorite variation with the same seed

Retrieve stock prices, exchange rates, cryptocurrency prices, company financial statements, and economic indicators through the Alpha Vantage API. It also covers historical data, news sentiment, and technical indicators, which summarize price and trading patterns.

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• Retrieve historical stock prices and trading volumes
• Collect company financial statements and earnings data
• Check foreign exchange and cryptocurrency prices

Design backend systems with clear boundaries between business rules, databases, and external services. Use Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to organize new applications, refactor existing code, and make core logic easier to test.

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• Planning the structure of a new backend
• Refactoring tightly coupled applications
• Testing business rules independently of external services

Helps process astronomical data in Python by converting coordinates, units, and time scales, working with FITS observation files, matching object catalogs, and calculating distances using cosmological models.

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• Converting celestial coordinates
• Reading and editing FITS observation files
• Matching objects across astronomical catalogs