Machine Learning Signal Processing Intern(Master/PhD)

Key Skills

Python Programming, SQL, Cloud computing

Job Description

Thermo Fisher Scientific leads molecular testing and molecular diagnostics with world-renowned real-time PCR, microarray, and capillary electrophoresis instrumentation systems. Our TaqPath COVID-19 solution has played a pivotal role in the COVID-19 pandemic. As we continue to expand our testing menu, multiplexing becomes a key requirement. The Genetic Sciences Division has an opportunity for an advanced Intern to investigate noise factors that impact multiplexing, modeling effects from dye chemistry, hardware and algorithms. Ultimately, you will deliver a visualization tool that makes these concepts accessible to R&D and allows them to in-silico experiment with different attributes that impact the system.

Division: Genetic Sciences Division (GSD)

Responsibilities

• Develop models for biotechnology data analysis that model instrumentation effects, chemistry, and molecular biology reactions. Use statistical modeling, machine learning, signal, and image processing techniques in designing the models.
• Develop visualization tools that facilitate the ability of algorithm developers and instrument operators to understand each other’s work.

Requirements

• Must be self-driven, must have a can-do attitude, must have an intense desire to build better products, must have a strong desire for new learning.
• A desire to build in-silico data science experimentation tools with high-quality visualization features.
• Master or PhD with a foundation in mathematics, backgrounds in computer science, machine learning, statistics, physics, biochemistry.
• Good understanding of algorithm development that is centered on concepts such as ML or Bayesian modeling.
• Proficient in Python, basic understanding of MATLAB and a willingness to work in other languages.