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Weekend Machine Learning Postdoc Jobs in Ashburn, VA

Senior Data Scientist

Washington, DC · On-site

$155K - $170K/yr

Use advanced statistics, modeling, and machine learning to predict outcomes and solve complex ... Work 40 hours a week but potentially work late night shifts and weekends at times to cover ...

Senior Data Scientist

Washington, DC · On-site

$155K - $170K/yr

Use advanced statistics, modeling, and machine learning to predict outcomes and solve complex ... Work 40 hours a week but potentially work late night shifts and weekends at times to cover ...

Understanding of machine learning concepts Education and Certifications: * Bachelors or Pursuing ... On June 15th, John only worked 4 hours because he left early for a long weekend. John's IBA was not ...

Understanding of machine learning concepts Education and Certifications: * Bachelors or Pursuing ... On June 15th, John only worked 4 hours because he left early for a long weekend. John's IBA was not ...

Understanding of machine learning concepts Education and Certifications: * Bachelors or Pursuing ... On June 15th, John only worked 4 hours because he left early for a long weekend. John's IBA was not ...

Knowledge of emerging technologies such as AI and machine learning. * Technical or cyber operations ... Must be able to work irregular hours, including nights, weekends, and holidays. * Travel required ...

Knowledge of emerging technologies such as AI and machine learning. * Technical or cyber operations ... Must be able to work irregular hours, including nights, weekends, and holidays. * Travel required ...

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Weekend Machine Learning Postdoc information

What is the difference between Weekend Machine Learning Postdoc vs Weekend Data Scientist?

AspectWeekend Machine Learning PostdocWeekend Data Scientist
Required CredentialsPhD in Computer Science, Machine Learning, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentAcademic research settings, universities, research labsIndustry companies, startups, consulting firms
Employer & Industry UsageResearch institutions, universities, academic grantsTech companies, finance, healthcare, retail
Common Search & ComparisonYesYes

The Weekend Machine Learning Postdoc typically involves academic research with a focus on advancing machine learning theories and models, often requiring a PhD. In contrast, a Weekend Data Scientist applies data analysis and machine learning techniques in industry settings, often with a bachelor's or master's degree. Both roles may work on similar projects but differ mainly in their environment, credentials, and end goals.

What are the typical projects and collaboration opportunities for a Weekend Machine Learning Postdoc?

As a Weekend Machine Learning Postdoc, you will often contribute to ongoing research projects, developing and refining machine learning models in collaboration with faculty, graduate students, and occasionally industry partners. While your hours are concentrated on weekends, you’ll typically participate in regular research meetings, code reviews, and may co-author papers or grant proposals. The role provides opportunities to mentor junior researchers and expand your expertise by working on interdisciplinary teams. This structure allows you to make significant research contributions while maintaining flexibility in your schedule.

What is a Weekend Machine Learning Postdoc?

A Weekend Machine Learning Postdoc is a postdoctoral researcher who focuses on machine learning projects and typically works on weekends or has a flexible schedule that includes weekend hours. This role often involves conducting advanced research in machine learning, developing algorithms, publishing papers, and collaborating with academic or industry teams. Weekend postdoc positions may be ideal for those balancing other commitments or seeking non-traditional work hours while continuing their research careers.

What are the key skills and qualifications needed to thrive as a Weekend Machine Learning Postdoc, and why are they important?

To thrive as a Weekend Machine Learning Postdoc, you need a strong background in machine learning, statistics, and programming, typically supported by a PhD in a relevant field. Experience with tools such as Python, TensorFlow, PyTorch, and data analysis platforms, as well as familiarity with academic research methodologies, is essential. Exceptional problem-solving abilities, self-motivation, and effective communication are vital soft skills for success in research and collaboration. These skills enable you to drive innovative research, efficiently manage independent projects, and contribute meaningful insights to the field.
What are the most commonly searched types of Machine Learning Postdoc jobs in Ashburn, VA? The most popular types of Machine Learning Postdoc jobs in Ashburn, VA are:
What are popular job titles related to Weekend Machine Learning Postdoc jobs in Ashburn, VA? For Weekend Machine Learning Postdoc jobs in Ashburn, VA, the most frequently searched job titles are:
What job categories do people searching Weekend Machine Learning Postdoc jobs in Ashburn, VA look for? The top searched job categories for Weekend Machine Learning Postdoc jobs in Ashburn, VA are:
Postdoctoral Fellow (PREP0004499)

Postdoctoral Fellow (PREP0004499)

Johns Hopkins University

Gaithersburg, MD • On-site

$53K - $72K/yr

Full-time

Re-posted 21 days ago


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Job description

Description
PREP Research Associate
This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
U.S. Citizen Preferred
Research Title:
Artificial Intelligence for Forensic Firearm and Toolmark Analysis
The work will entail:
The Sensor Science Division at the National Institute of Standards and Technology (NIST) is seeking a researcher to advance the application and scientific understanding of Artificial Intelligence and Machine Learning (AI/ML) in forensic firearm and toolmark analysis. Forensic examiners compare toolmarks on cartridge cases or bullets to evaluate whether they were fired from the same firearm. A similar comparison is made with marks from other tools, such as pliers and additive manufacturing systems (e.g. 3D printers). These analyses are currently subjective and rely heavily on examiner expertise. This position will lead the development, evaluation, and characterization of AI/ML methods to improve the objectivity, reproducibility, and accuracy of toolmark pattern evidence analysis. The researcher will address critical challenges in the application of AI/ML to forensic science, including transparency, robustness, and bias, through the development of guidelines for training and validation datasets; procedures to rigorously characterize model performance, uncertainty, and operational limitations; and approaches to provide insight into model decision-making processes. The researcher will collaborate with interdisciplinary teams and communicate findings through technical reports, publications, and presentations, contributing to the development of scientifically grounded and standards-based approaches for forensic evidence evaluation.
Responsibilities include but are not limited to:
1) Develop a forward-looking research program on AI/ML in forensic firearm and toolmark analysis and collaborate on cross-cutting techniques for other types of pattern evidence.
2) Lead the development of a computational pipeline for the consistent segmentation of toolmark images using AI/ML methods.
3) Investigate application of AI/ML to address major challenges in forensic toolmark analysis, such as characterizing toolmark quality and, ultimately, the direct comparison of toolmark images.
4) Benchmark AI/ML-assisted results against those obtained with procedural algorithms and traditional human examinations. Investigate where AI/ML can provide the most significant improvements in objectivity and efficiency.
5) Investigate approaches for quantifying the uncertainty of AI/ML outputs to ensure objective communication of the strength of the evidence in courtroom testimony. Explore the feasibility of explainable AI (XAI) frameworks to inform examiners on the toolmark features that drive the model's output.
6) Collaborate with the forensic community to translate research findings into actionable standards and best practice guides.
7) Publish research findings in peer-reviewed journals and present results at scientific conferences.
Qualifications
1) Ph.D. or master's degree in computer science, physics, engineering, statistics, forensic science, or a closely related field.
2) Research experience in the development and application of AI/ML for image analysis.
3) Proficiency with Python or MATLAB.
4) Evidence of independent research experience and a strong enthusiasm for learning new theoretical, computational, and experimental techniques.
5) Strong oral and written communication skills.
6) U.S. Citizenship preferred.
Application Instructions
Please upload the following with your application:
• CV/Resume
*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. Your resume will not be considered if the following information is included on your CV/resume.
Self portraits
Phone number
Home address/Country
Citizenship status
Languages spoken
Sex/Gender
Privacy Act Statement
Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.

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