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Physics Based Machine Learning Jobs in Hawaii (NOW HIRING)

... Machine Learning, Information Systems, Operations Research, Physics, Computational Biology, etc ... At Cymertek, employment decisions are made based on merit, qualifications, and business needs ...

... physics, chemistry, biology, astronomy), or other science disciplines with a substantial ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

Data Scientist 2

Honolulu, HI ยท On-site

$98K - $108K/yr

... physics, chemistry, biology, astronomy), or other science disciplines with a substantial ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

... machine learning, and statistical modeling techniques to large and complex datasets * Experience developing and managing data pipelines, model pipelines, and cloud-based architectures (AWS, Azure, or ...

SIMILAR CAREER TITLES Machine Learning Engineer, Artificial Intelligence Engineer, Data Scientist ... Familiarity with cloud-based AI tools * Skill in debugging and testing AI models DESIRED SKILLS

SIMILAR CAREER TITLES Data Analyst, Machine Learning Engineer, Data Engineer, Business Intelligence ... Physics, Operations Research, Information Technology, etc. ALTERNATE EXPERIENCE General comment on ...

Experience with machine learning frameworks like scikit-learn, TensorFlow, or PyTorch might be ... Actual compensation may vary based on factors such as job responsibilities, education, experience ...

OSINT Data Scientist

Honolulu, HI ยท On-site

$77K - $176K/yr

Knowledge of machine learning, AI, or Natural Language Processing (NLP) * Knowledge of text mining ... However, we want to ensure a fair candidate process based on your own skills and knowledge. As part ...

Analytic Cloud Developer

Honolulu, HI ยท On-site

$55.50 - $76/hr

Integrate cloud-based tools * Ensure cloud security compliance * Optimize data processing pipelines ... Experience with machine learning * Understanding of big data frameworks * Strong collaboration and ...

Data Scientist

Aiea, HI

$141K - $236K/yr

In this role you will support cutting-edge analytics, machine learning, and data engineering ... Working knowledge of Agile development methodologies and Git-based version control Clearance ...

Requires strong technical and computational skills - engineering, physics, mathematics, coupled ... Experience with machine learning, algorithm analysis, and data clustering. Peraton Overview Peraton ...

Showing results 41-60

Physics Based Machine Learning information

What does a physics based machine learning professional do?

Physics Based Machine Learning professionals often work on projects that involve applying machine learning techniques to physical systems, such as improving simulations in engineering, optimizing energy systems, or accelerating scientific research through data-driven modeling. Daily tasks might include developing algorithms that incorporate physical laws, analyzing simulation data, and collaborating with experts from engineering, data science, or research teams. The role can involve both theoretical and hands-on work, often requiring iterative testing and validation. This environment provides opportunities to tackle cutting-edge challenges, contribute to innovation, and potentially lead to career paths in research, product development, or advanced analytics.

What is a physics based machine learning?

A Physics Based Machine Learning job involves developing machine learning models that incorporate physical laws and domain knowledge to improve predictions and interpretability. Professionals in this field work at the intersection of physics, data science, and artificial intelligence to create models that are more robust, generalizable, and efficient, especially in scientific and engineering applications. Responsibilities often include data analysis, algorithm development, numerical simulations, and integrating physics-based constraints into ML models. These roles are common in industries like climate science, robotics, materials science, and computational physics.

What are the key skills and qualifications needed to thrive in physics based machine learning?

To thrive in Physics Based Machine Learning, you need advanced knowledge of physics, strong programming skills (Python, MATLAB, or C++), and a deep understanding of machine learning and statistical modeling, typically supported by a master's or PhD in physics, engineering, or a related field. Familiarity with simulation software, scientific computing libraries (such as TensorFlow, PyTorch, NumPy), and version control systems is essential. Strong problem-solving ability, effective communication, and cross-disciplinary collaboration skills set outstanding candidates apart. These competencies are crucial for designing robust, real-world models that integrate physical principles with data-driven techniques to solve complex problems.

What are popular job titles related to Physics Based Machine Learning jobs in Hawaii? For Physics Based Machine Learning jobs in Hawaii, the most frequently searched job titles are:
What cities in Hawaii are hiring for Physics Based Machine Learning jobs? Cities in Hawaii with the most Physics Based Machine Learning job openings:

Data Scientist 2 with Security Clearance

GRVTY

Honolulu, HI โ€ข On-site

Other

Re-posted 3 days ago


Job description

What You'll be Owning: * We are actively searching for Data Scientists, located in Hawaii, to support our team. We have varying levels of Data Scientist roles, depending on years of experience and education. * Performs tasks associated with Big Data Platform management, utilizes skills in programming languages, develops prototype algorithms as well as algorithm refinements, and supports data visualization and analytics. What You Must Have : * Bachelor's Degree with 3 years of relevant experience OR Associates degree with 5 years of relevant experience * Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, , data structures, data mining, artificial intelligence). College-level requirements, or upper-level math courses designated as elementary or basic do not count. Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university. * Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python)), statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g., data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than one area is strongly preferred * Active TS/SCI w/poly What Would Be Nice to Have: * Foundations: (Mathematical, Computational, Statistical) 2. Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility) * Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations) * Devise strategies for extracting meaning and value from large datasets. Make and communicate principled conclusions from data using elements of mathematics, * Statistics, computer science, and application specific knowledge. * Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in data holdings. * Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data. Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting, processing, storage and analytic capabilities and limitations.