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Scientific Machine Learning Jobs in Maine (NOW HIRING)

Northeastern University

Data Scientist

Portland, ME · On-site

... and compare machine learning models under supervision. • Assist with model validation ... D. (optional) in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely ...

Northeastern University

Data Scientist

Portland, ME · On-site

$87K - $123K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University ... Hands-on experience with classical machine learning methods such as linear/logistic regression ...

NorthEastern

Data Scientist

Portland, ME · On-site

$87K - $123K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Data Scientist at the AI Solutions Hub (AISH), the delivery arm of Northeastern University ... Hands-on experience with classical machine learning methods such as linear/logistic regression ...

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 ...

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 ...

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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 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 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 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 Maine?

For Scientific Machine Learning jobs in Maine, the most frequently searched job titles are:

What job categories do people searching Scientific Machine Learning jobs in Maine look for?

The top searched job categories for Scientific Machine Learning jobs in Maine are:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Maine as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 21% Part Time, 3% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Data Scientist

Northeastern University

Portland, ME • On-site

Full-time

Re-posted 26 days ago

Job description

Job Summary:
Northeastern University is seeking a Data Scientist for a full-time, one-year term appointment at their Roux Institute in Portland, Maine. The role focuses on supporting the development and delivery of AI and data science solutions, involving data analysis, feature engineering, model development, and collaboration with senior professionals in the field.
Responsibilities:
• Perform data cleaning, exploratory data analysis (EDA), and feature engineering.
• Train, evaluate, and compare machine learning models under supervision.
• Assist with model validation, performance monitoring, and documentation.
• Contribute to ML pipelines and collaborate with ML engineers on deployment-related tasks.
• Ability to clearly communicate analytical findings to technical and non-technical audiences with guidance.
• Collaborate effectively with cross-functional teams including data scientists, engineers, project managers, and faculty experts.
• Willingness to participate in client meetings in a supporting role.
Qualifications:
Required:
• Master’s degree (required) or Ph.D. (optional) in Computer Science, Engineering, Applied Mathematics, Statistics, or a closely related field.
• 0–2 years of industry, research, or applied project experience in data science or machine learning.
• Experience gained through internships, co-ops, academic research, or applied capstone projects is acceptable.
• Solid understanding of statistical methods, regression, hypothesis testing, and basic experimental design.
• Hands-on experience with classical machine learning methods such as linear/logistic regression, decision trees, and gradient boosting.
• Familiarity with deep learning concepts and modern architectures (e.g., convolutional neural networks or transformers); deep specialization is not required.
• Proficiency in Python for data analysis and model development (NumPy, pandas, scikit-learn).
• Working knowledge of SQL and relational databases.
• Familiarity with at least one ML or deep learning framework (e.g., PyTorch, TensorFlow, HuggingFace).
• Ability to clearly communicate analytical findings to technical and non-technical audiences with guidance.
• Collaborate effectively with cross-functional teams including data scientists, engineers, project managers, and faculty experts.
• Willingness to participate in client meetings in a supporting role.
• Awareness of ethical AI principles including fairness, transparency, and responsible model use.
• Willingness to follow established governance, documentation, and review practices.
• Strong curiosity and motivation to learn new tools, techniques, and AI methods.
• Openness to feedback and mentorship.
• Ability to manage assigned tasks, meet deadlines, and maintain high-quality work.
• Proactive attitude and willingness to take increasing responsibility over time.
Preferred:
• Industry experience is preferred.
• Exposure to NLP, computer vision, or speech processing through coursework or academic/industry projects.
• Familiarity with cloud platforms (AWS, Azure, or GCP).
• Understanding of software development best practices such as version control (Git) and Agile workflows.
Company:
Founded in 1898, Northeastern is a global research university with a distinctive, experience-driven approach to education and discovery. Founded in 1898, the company is headquartered in Boston, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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