Interested in this Research Scientist role at Columbia University?
Apply Now →Skills & Technologies
About This Role
THE KUO LAB is seeking an outstanding Associate Research Scientist with expertise in human electroencephalography (EEG) to join the Initiative for Columbia Ataxia and Tremor (ICAT) Laboratory. The successful candidate will lead and support translational research focused on cerebellar ataxia, tremor, Parkinson's disease, and other movement disorders through advanced EEG acquisition, analysis, and integration with multimodal clinical and neurophysiological data. The Associate Research Scientist will work closely with the Principal Investigator, multidisciplinary clinical teams, engineers, and data scientists to develop innovative EEG biomarkers of disease progression, neural circuit dysfunction, and therapeutic response. This position offers opportunities to lead independent research projects, publish in high\-impact journals, mentor trainees, and contribute to grant development.
JOB RESPONSIBILITIES:
- Design, implement, and oversee human EEG research studies involving patients with movement disorders and healthy controls.
- Develop and optimize EEG acquisition protocols, including resting\-state, task\-based, and event\-related potential (ERP) paradigms.
- Perform advanced EEG preprocessing, artifact removal, source localization, time\-frequency analyses, connectivity analyses, and machine learning approaches.
- Integrate EEG findings with clinical, neuroimaging, behavioral, and genetic datasets.
- Develop novel neurophysiological biomarkers for cerebellar ataxia, essential tremor, Parkinson's disease, dystonia, and related disorders.
- Maintain quality assurance procedures for EEG data collection and processing.
- Supervise research coordinators, graduate students, postdoctoral fellows, and research assistants involved in EEG studies.
- Prepare manuscripts for peer\-reviewed publications and present research findings at national and international scientific meetings.
- Assist in writing NIH and foundation grant applications.
- Collaborate with investigators across Columbia University and external research institutions.
- Ensure compliance with IRB regulations, HIPAA requirements, and Good Clinical Practice (GCP) guidelines.
- Participate in laboratory meetings, journal clubs, and collaborative research initiatives.
- Other duties as assigned
MINIMUM QUALIFICATIONS:
- Ph.D. in Neuroscience, Biomedical Engineering, Psychology, Electrical Engineering, or a closely related field.
- Minimum of three years of postdoctoral research experience or equivalent.
- Demonstrated expertise in human EEG acquisition and advanced EEG signal processing.
- Strong publication record in peer\-reviewed scientific journals.
- Experience analyzing electrophysiological data using MATLAB, Python, EEGLAB, FieldTrip, MNE\-Python, or similar software.
- Excellent written and verbal communication skills.
- Ability to work independently while contributing effectively within a multidisciplinary research environment.
PREFERRED QUALIFICATIONS:
- Experience conducting EEG research in neurological or movement disorders.
- Knowledge of cerebellar physiology and motor control.
- Experience with event\-related potentials (ERP), source localization, functional connectivity, and neural oscillation analyses.
- Familiarity with statistical analysis software (R, SPSS, Python).
- Experience with machine learning or artificial intelligence approaches applied to EEG.
- Experience integrating EEG with MRI, motion capture, EMG, wearable sensors, or other neurophysiological modalities.
- Prior experience mentoring trainees and managing collaborative research projects.
- Successful history of obtaining research funding or contributing to NIH grant applications.
instructions
Applicants are required to create an applicant profile and upload a CV and Cover Letter in Columbia’s online Academic Search and Recruiting (ASR) system. Preferred CV formatting guidelines: https://www.vagelos.columbia.edu/file/41228/download?token\=JJuDEmY6
Columbia University is an Equal Opportunity Employer / Disability / Veteran
Pay Transparency Disclosure
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University’s good faith and reasonable estimate of the range of possible compensation at the time of posting.
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 4,317 AI roles we're tracking, Research Scientist positions make up 4% of the market. At Columbia 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 $222,200 based on 378 positions with disclosed compensation. Entry-level AI roles across all categories have a median of $110,000.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Columbia University AI Hiring
Columbia University has 1 open AI role right now. They're hiring across Research Scientist. Based in US.
Location Context
AI roles in Austin pay a median of $214,343 across 143 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.