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Weekend Machine Learning Postdoc Jobs in New York

Postdoctoral Fellow-MSH

Manhattan, NY · On-site

$53K - $73K/yr

... researchers to join our team as Postdoctoral Scholars to work on NIH-funded research in ... A major component of this work will rely on applying machine learning methods to large-scale ...

Description POSTDOCTORAL ASSOCIATE New York University Tandon School of Engineering The Department ... machine learning as exemplified by a strong publication record. Previous experience on applied and ...

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Weekend Machine Learning Postdoc information

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 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 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 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 most commonly searched types of Machine Learning Postdoc jobs in New York?

The most popular types of Machine Learning Postdoc jobs in New York are:

What are popular job titles related to Weekend Machine Learning Postdoc jobs in New York?

For Weekend Machine Learning Postdoc jobs in New York, the most frequently searched job titles are:

What job categories do people searching Weekend Machine Learning Postdoc jobs in New York look for?

The top searched job categories for Weekend Machine Learning Postdoc jobs in New York are:

What cities in New York are hiring for Weekend Machine Learning Postdoc jobs?

Cities in New York with the most Weekend Machine Learning Postdoc job openings:

Infographic showing various Weekend Machine Learning Postdoc job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Postdoctoral Research Associate -- AI-Driven Reactive Robotics for Radioisotope Production

Manhattan, NY • On-site

Brookhaven National Laboratory
Scientific Research and Development Services • 1 - 5K employees

$71K - $85K/yr

Other

Posted 9 days ago


Key responsibilities

  • Design and build a dual-system robotic architecture that includes a vision-language model for task planning and a reactive control system for fine-motor manipulation.

  • Develop the fast reactive control layer for fluid manipulation, including tasks such as pipetting and pouring, with real-time correction capabilities.

  • Build and validate a 3D perception stack for fluid-state estimation through transparent and reflective glassware before working with active materials.


Job description

## Postdoctoral Research Associate — AI-Driven Reactive Robotics for Radioisotope ProductionApplylocations: Upton, NYtime type: Full timeposted on: Posted Yesterdayjob requisition id: JR102615The Isotope Research & Production (IP) program at Brookhaven National Laboratory has an opening for a postdoctoral researcher to develop an AI-driven robotic system for the chemical purification steps in radioisotope production. The scientific challenge is not “can a robot move a beaker,” which is largely solved, but the open problem underneath it: fast, reactive fine-motor manipulation of fluids, precision pipetting, and pouring that corrects in real time when liquid begins to slosh or spill; coupled to a frontier vision-language model that plans and supervises the multi-step workflow. The successful candidate will have wide latitude to shape the research direction and will publish contributions to reactive, generalizable robotic manipulation in unstructured laboratory environments.This position sits at the intersection of a mission-driven isotope-production program and frontier machine learning, and has a high level of interaction with an interdisciplinary scientific community spanning robotics, radiochemistry, and computing.**Essential Duties and Responsibilities:*** Design and build a dual-system robotic architecture: a frontier vision-language model for task planning, affordance reasoning, and anomaly/stop-gating, coupled to a fast learned controller for reactive fine-motor manipulation.* Develop the fast reactive control layer using an approach matched to your background (e.g. force-feedback MPC with a learned motion prior, latent world models, imitation/vision-language-action policies, or continuous-time neural control).* Build the 3D perception stack for fluid-state estimation (fill level, meniscus, vessel pose) through transparent, reflective glassware, using pretrained visual encoders.* Develop and validate on a cold bench (water and glassware) before any active material.* Publish results in peer-reviewed venues and present at conferences.**Required Knowledge, Skills, and Abilities:*** Ph.D. in mechanical engineering, electrical engineering, computer science, physics, mathematics, statistics/data science, or a closely related technical field* Backgrounds in robotics, controls, or machine learning are especially relevant.* Strong programming skills in Python and hands-on experience with modern ML frameworks (e.g. PyTorch).* Hands-on problem-solving skills and clear, concise written and verbal communication.* Demonstrated record of peer-reviewed publication.* Ability to work independently and drive an open-ended, high-risk/high-reward research agenda.**Preferred Knowledge, Skills, and Abilities:*** Experience in one or more of: robotic manipulation, reinforcement learning, imitation learning, world models, model-predictive/optimal control, or continuous-time dynamical systems.* Demonstrated record of peer-reviewed publication, ideally as a lead (first or primary) author.* Experience with collaborative robot arms (e.g. UFactory xArm) and force/torque sensing.* Experience with vision-language(-action) models, diffusion/flow-matching policies, or JEPA-style latent representations.* Familiarity with 3D vision and pretrained visual encoders (e.g. DINOv2, V-JEPA).* Interest in or exposure to laboratory automation, chemistry workflows, or radiochemistry.* Track record of conference presentation.**Environmental, Health & Safety Requirements:**Work is performed initially on a non-radioactive cold bench (water and glassware). Work with active material is a later project phase and would require applicable radiological worker training and adherence to BNL radiological control and laboratory safety procedures.**Other Information:*** This position is located at BNL in Upton, New York.* Initial 2-year term appointment subject to renewal contingent on performance and funding.* BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a combined total of 5 years of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events.* Candidates must have completed all degree requirements by the commencement of the employment.* Please submit a cover letter and CV (including a list of publications).Brookhaven National Laboratory is committed to providing fair, equitable and competitive compensation. The full salary range for this position is $71900 - $85000 / year. Salary offers will be commensurate with the final candidate’s qualification, education and experience and considered with the internal peer group. #J-18808-Ljbffr