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About This Role
Applications are invited for an individual to be appointed as a part\-time Associate Research Scientist in The Weiss Lab at NYU Chemistry. The chosen candidate will be responsible for performing the following duties:
- Integration of automation in BSL\-1/2\+ labs.
- Robotic liquid handling \& custom robotic design and integration: This role will develop custom stepper and BLDC motor drivers for FOC control of multi\-stage robotic systems.
- Remote Monitoring \& IoT. Using MQTT brokers and Firebase, the engineer will build systems to monitor incubator CO2 levels, temperature, and door states.
- Custom Control Circuits: You’ll design custom interfaces that allow remote systems to trigger physical actions in the lab, such as operating equipment or moving samples.
- Frontier Single\-Molecule Live Imaging.
- High\-Speed Data Pipelines: This role will manage the interfaces to ensure that terabytes of real\-time high\-speed data are stored correctly without data loss.
- Hardware Synchronization: This role will ensure the amplification stages and MOSFET\-based device are synchronized at near\-ns resolution.
In compliance with NYC’s Pay Transparency Act, the annual base salary for this role is $26/hr. New York University considers factors such as (but not limited to) the specific grant funding and the terms of the research grant when extending an offer.
This position is based in New York, and the selected candidate will be expected to work onsite as of their effective start date.
Mechanical engineering expertise \- Master’s degree or higher. Serve as the domain expert and primary collaborator with biology experts working on building systems that require advanced ME, robotics, and mechatronics knowledge.
Experience with computer hardware communication bus protocols: USB, I2C, I2S, CSI, Ethernet, SPI, PCIe, HDMI, CAN, serial comms, etc
Strong communication \- You can explain complex physical behavior clearly, write structured technical reports, and align cross\-functional teams around root causes and next steps
Experience with:
Mechanical Engineering \& Simulation: Ansys Fluent / CFX, Abaqus, COMSOL Multiphysics, OpenFOAM, MATLAB \& Simulink
IoT \& Embedded Systems: Firebase (Realtime DB, Auth, FCM), MQTT/Mosquitto Broker, PubSubClient, Arduino IDE, NodeMCU Firmware, SIM800L/SIM900f GSM Modules
Programming \& Development Environments: Linux, Anaconda3, cmder, Jupyter Notebook, Google Colab, GitHub
CAD \& Design: SolidWorks, ROS2 (Robot Simulation \& Offline Programming), Microsoft Office Suite
Programming Languages: Data Science \& Machine Learning: Python (Pandas, NumPy, Matplotlib, Seaborn, Keras, TensorFlow, PyTorch) Systems \& Networking: C, C\+\+ (TCP/IP Protocols, LAN/WAN/MPLS Systems)
Cloud Services: Google Firebase (Firestore, Auth, FCM Messaging), SQLite, RESTful APIs
DevOps \& Deployment: GitHub, Netlify (CI/CD for React), Heroku (Python App Hosting), modular API schema for team\-based dev
Microcontrollers: ESP8266 NodeMCU, Arduino Uno, Raspberry Pi
Electrical Components: Oscilloscopes, Function Generators, DC Power Supplies, DMMs, Wave Generator, DC Motor, Tacho Generator, Incremental \& Gray Encoders, Potentiometers
IoT Sensors \& Devices: MQ2 Gas Sensor, DHT11/DHT20 Temp \& Humidity, Hall Effect Magnetic Sensor, PIR Motion Sensor, LIBO Electronic Deadbolt Lock, LCD Displays, 4x4 Keypads, RGB LEDs, Relay Modules
To be considered, all applicants must submit a cover letter summarizing their research experience and specifying their interest in this position, a curriculum vitae, and two contact references.
For people in the EU, click here for information on your privacy rights under GDPR: www.nyu.edu/it/gdpr
NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, reproductive health decision making, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. All interested persons are encouraged to apply for vacant positions at all levels.
Sustainability Statement
NYU aims to be among the greenest urban campuses in the country and carbon neutral by 2040\. Learn more at nyu.edu/sustainability
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 3,823 AI roles we're tracking, Research Scientist positions make up 3% of the market. At New York University, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $223,400 based on 280 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $97,880.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
New York University AI Hiring
New York University has 2 open AI roles right now. They're hiring across Research Scientist. Based in New York, NY, US. Compensation range: $61K - $61K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national median.
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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