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Scientific Machine Learning Jobs in Baltimore, MD

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Scientific Machine Learning information

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How much do scientific machine learning jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for scientific machine learning in Baltimore, MD is $31.28, according to ZipRecruiter salary data. Most workers in this role earn between $19.09 and $39.90 per hour, depending on experience, location, and employer.

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 Baltimore, MD? For Scientific Machine Learning jobs in Baltimore, MD, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Baltimore, MD look for? The top searched job categories for Scientific Machine Learning jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Scientific Machine Learning jobs? Cities near Baltimore, MD with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Baltimore, MD as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $65,056 per year, or $31.3 per hour.

Asst Prof Machine Learning

University of Maryland, Baltimore

Baltimore, MD • On-site

$17 - $19.75/hr

Full-time

Re-posted 9 days ago


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Job description

Job Description
The Imaging Computing Laboratory at the Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine is looking for a candidate to fill an Assistant Professor position in machine learning based medical image processing. This position is in the non-tenure track. The research focuses will include: deep learning-based MRI image reconstruction, deep learning based arterial spin labeling perfusion MRI processing, and resting state fMRI processing. Ideal candidates should have a PhD in computer science, biomedical engineering, or electrical engineering. Over three years of research experience in deep learning, MRI and medical image processing is preferred.
Candidates should submit a full CV, a cover letter, and names of three referees who can provide recommendation letters to
Qualifications
For immediate consideration, please send a cover letter and a recent CV, including names and contact information of three references to the following link:
UMB is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy.
We value diversity and how it enriches our academic and scientific community and strive toward cultivating an inclusive environment that supports all employees.

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