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Scientific Machine Learning Jobs in Vermont (NOW HIRING)

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

Whiterabbit.ai

As a Research Scientist Intern at Whiterabbit.ai, you will: * Play a key role in architecting the ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

Green Mountain Power

Data Engineer

Colchester, VT · On-site +1

$145K - $150K/yr

Build, validate, and deploy machine learning models and algorithms using best practices in data science and reproducible research. Apply statistical modeling, machine learning, and predictive ...

Pwc

AI Solutions Engineering Delivery Lead

Montpelier, VT · On-site

$103K - $136K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Pwc

CTIO AI Engineering Manager

Montpelier, VT · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Vermont

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a scientific machine learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Vermont? For Scientific Machine Learning jobs in Vermont, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Vermont look for? The top searched job categories for Scientific Machine Learning jobs in Vermont are:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Vermont as of July 2026, with employment types broken down into 1% As Needed, 70% Full Time, 27% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Research Scientist Intern (2025)

Whiterabbit.ai

Colchester, VT • On-site

Other

Re-posted 20 days ago

Job description

We are looking for a Research Scientist Intern to push the state of the art of our AI models. As a Research Scientist Intern at Whiterabbit.ai, you will:

  • Play a key role in architecting the algorithms and models that will power our products
  • Train on a dedicated high-performance compute cluster specialized for deep learning research
  • Work with doctors and healthcare professionals to identify serious problems and leverage their domain expertise to build robust solutions
  • Remain an active contributor to the research community by partnering with universities and publishing high impact papers

Who we are:

Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection of cancer with artificial intelligence. We collaborate closely with one of the top medical schools in the country and have exclusive access to one of the world’s largest cancer datasets with millions of images. We invent algorithms that make doctors more productive, more accurate, and more capable. We build products and services with a relentless focus on transforming the patient’s healthcare experience.

Responsibilities

  • Develop highly scalable classifiers and detectors that solve real-world problems
  • Learn and understand a large body of research in deep learning and machine learning
  • Participate in cutting-edge research for medical applications of computer vision

Must Have Experience

  • Experience with deep learning and convolutional networks
  • Strong theoretical and empirical research background
  • Fluency with a deep learning framework and Python

Nice to Have Experience

  • Contributions to research communities and efforts, such as publications at conferences like CVPR, NeurIPS, ICCV, ECCV, ICML, and ICLR
  • Large scale machine learning experience working with terabytes of data
  • Implemented custom operations/modules in a deep learning framework
  • Imagination, ambition, and curiosity

Apply