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Internship Machine Learning Neuroscience Jobs in Connecticut

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$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

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Internship Machine Learning Neuroscience information

What are the key skills and qualifications needed to thrive as an Internship Machine Learning Neuroscience, and why are they important?

To thrive in an Internship Machine Learning Neuroscience role, you generally need a background in neuroscience, computer science, or a related field, along with a solid understanding of machine learning concepts. Experience with programming languages such as Python, libraries like TensorFlow or PyTorch, and familiarity with neuroimaging software are commonly required. Strong analytical thinking, problem-solving skills, and effective communication help you work collaboratively and adapt to complex research environments. These skills are essential for contributing meaningfully to interdisciplinary projects at the intersection of neuroscience and artificial intelligence.

What is the difference between Internship Machine Learning Neuroscience vs Internship Data Science?

AspectInternship Machine Learning NeuroscienceInternship Data Science
Required CredentialsBackground in neuroscience, machine learning, programmingBackground in statistics, programming, data analysis
Work EnvironmentResearch labs, healthcare, academia, tech companiesBusiness, tech firms, research institutions
Industry UsageNeuroscience research, AI development, healthcare techBusiness analytics, product development, consulting

Internship Machine Learning Neuroscience focuses on applying machine learning techniques to neuroscience data, often within research or healthcare settings. In contrast, Internship Data Science covers a broader range of data analysis across industries. Both roles require programming skills, but the focus and industry applications differ significantly.

What is an Internship in Machine Learning Neuroscience?

An Internship in Machine Learning Neuroscience is a temporary position, often for students or recent graduates, that involves applying machine learning techniques to neuroscience research. Interns may work on projects such as analyzing brain imaging data, modeling neural networks, or developing algorithms to understand brain function. These internships provide hands-on experience in both computational methods and neuroscience concepts, helping interns build valuable skills for future academic or industry roles. Opportunities can be found in universities, research institutes, or technology companies with neuroscience divisions.

What types of projects do interns typically work on in a Machine Learning Neuroscience internship?

Interns in Machine Learning Neuroscience often engage in projects that combine data analysis, algorithm development, and neuroscience research. This can include tasks such as preprocessing neural data, building and evaluating machine learning models to interpret brain signals, or developing tools for data visualization. Interns frequently collaborate with both data scientists and neuroscientists, gaining hands-on experience with real-world datasets and exposure to interdisciplinary research environments. These projects help interns build practical skills and contribute meaningful insights to ongoing research.
What are the most commonly searched types of Machine Learning Neuroscience jobs in Connecticut? The most popular types of Machine Learning Neuroscience jobs in Connecticut are:
What cities in Connecticut are hiring for Internship Machine Learning Neuroscience jobs? Cities in Connecticut with the most Internship Machine Learning Neuroscience job openings:
Internship Machine Learning Neuroscience jobs near you

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International, LLC

Stamford, CT • On-site

Full-time

Posted 12 days ago

Job description

Application Deadline: September 1, 11:59pm EST
Program Summary - Commercial Technology Internships
Company Overview:
Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.
Position Overview:
CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.
Responsibilities:
  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:
  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

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