A strong analytic background, particularly in modeling neural systems and analyzing large datasets. * Experience with acoustic signal processing, sound recognition, and machine learning. APPOINTMENT ...
A strong analytic background, particularly in modeling neural systems and analyzing large datasets. * Experience with acoustic signal processing, sound recognition, and machine learning. APPOINTMENT ...
Cloud Production Engineer, Sports (Contractor)
Stamford, CT · On-site
$59.50 - $79.50/hr
Monitor signal flow, stream health, and system performance during live events * Assist with setup ... Contribute to documentation, process improvement, and knowledge sharing * Perform system updates ...
Cloud Production Engineer, Sports (Contractor)
Stamford, CT · On-site
$59.50 - $79.50/hr
Monitor signal flow, stream health, and system performance during live events * Assist with setup ... Contribute to documentation, process improvement, and knowledge sharing * Perform system updates ...
Cloud Production Engineer, Sports (Contractor)
Stamford, CT · On-site
$59.50 - $79.50/hr
Monitor signal flow, stream health, and system performance during live events * Assist with setup ... Contribute to documentation, process improvement, and knowledge sharing * Perform system updates ...
Cloud Production Engineer, Sports (Contractor)
Stamford, CT · On-site
$59.50 - $79.50/hr
Monitor signal flow, stream health, and system performance during live events * Assist with setup ... Contribute to documentation, process improvement, and knowledge sharing * Perform system updates ...
Eeg Neural Signal Processing information
What is EEG neural signal processing?
EEG neural signal processing refers to the analysis and interpretation of electrical activity in the brain as recorded by electroencephalography (EEG). This process involves filtering, amplifying, and extracting meaningful features from the raw EEG signals to study brain function, diagnose neurological disorders, or develop brain-computer interfaces. Researchers and clinicians use various computational techniques to separate noise from actual brain signals, enabling a better understanding of brain activity and aiding in medical or research applications.
What are the key skills and qualifications needed to thrive as an EEG neural signal processing specialist?
To thrive as an EEG Neural Signal Processing specialist, you need a solid background in neuroscience, signal processing, and programming, typically supported by a degree in biomedical engineering, neuroscience, or related fields. Familiarity with technical tools such as MATLAB, Python, EEGLAB, and experience with EEG acquisition systems are essential. Strong analytical thinking, problem-solving skills, and clear communication help you interpret complex data and collaborate with interdisciplinary teams. These skills are crucial for accurately analyzing neural signals, advancing research, and ensuring reliable outcomes in clinical or research settings.
What are some common challenges faced when processing EEG neural signals, and how can professionals address them in their daily work?
One of the main challenges in EEG neural signal processing is dealing with noise and artifacts, such as those caused by eye movements or muscle activity, which can obscure the true neural signals. Professionals often use specialized filtering techniques and artifact rejection algorithms to clean the data before analysis. Additionally, interpreting the complex and high-dimensional EEG data requires a solid understanding of both neuroscience and advanced signal processing methods. Collaborating closely with neuroscientists, clinicians, and software engineers is crucial for refining analysis pipelines and ensuring meaningful results.
What is the difference between Eeg Neural Signal Processing vs Neurophysiologist?
| Aspect | Eeg Neural Signal Processing | Neurophysiologist |
|---|---|---|
| Required Credentials | Typically requires a degree in neuroscience, biomedical engineering, or related fields; certifications in signal processing are a plus | Requires advanced degrees (PhD or MD), specialized training in neurophysiology, and often board certification |
| Work Environment | Research labs, hospitals, or tech companies focusing on brain signal analysis | Hospitals, clinics, research institutions conducting neurological assessments |
| Industry Usage | Primarily in research, medical device development, and data analysis | Clinical diagnosis, patient care, and neurological research |
While Eeg Neural Signal Processing focuses on analyzing brain signals using signal processing techniques, Neurophysiologists perform clinical assessments and interpret neurological data. Both roles require a strong background in neuroscience, but neurophysiologists typically have more clinical responsibilities and advanced medical credentials.
What are popular job titles related to Eeg Neural Signal Processing jobs in Connecticut?
For Eeg Neural Signal Processing jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Eeg Neural Signal Processing jobs in Connecticut look for?
The top searched job categories for Eeg Neural Signal Processing jobs in Connecticut are:
What cities in Connecticut are hiring for Eeg Neural Signal Processing jobs?
Cities in Connecticut with the most Eeg Neural Signal Processing job openings:
Full-time
Re-posted 21 days ago
University Of Connecticut rating
9.3
Based on 10 frontline employees who took The Breakroom Quiz
9th of 620 rated colleges and universities
Job description
Postdoctoral Research Associate
Search #: 499299
Work type: Full-time
Location: UConn Storrs
Categories: Research, Postdoctoral Research Associates
JOB SUMMARY
The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecticut seeks applicants for a postdoctoral position in systems and computational neuroscience.
DUTIES AND RESPONSIBILITIES
We are seeking highly motivated and creative applicants who can lead a project on Misophonia, a psychological and behavioral disorder in which individuals experience adverse emotional reactions to specific sounds ("auditory triggers"). The broad project goal is to develop computational models of hearing and perception that are fitted to human perceptual measurements and that can be used to characterize and diagnose misophonia. The models will also be used to develop sound processing tools to remove and de-emphasize auditory triggers (e.g., with headphones) and improve participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing.
UConn has a vibrant neuroscience community, and there are opportunities for collaboration between departments, institutes, and Universities involved in the project. The primary appointment is in Biomedical Engineering and/or Electrical Engineering. The work will be conducted in collaboration with the Behavioral Neuroscience program in the Psychological Sciences department (Ian Stevenson), the Electrical and Computer Engineering/Biomedical Engineering departments at the University of Connecticut (Monty Escabí), and the Connecticut Institute for Brain and Cognitive Sciences.
MINIMUM QUALIFICATIONS
PREFERRED QUALIFICATIONS
APPOINTMENT TERMS
This is a full-time, 12-month position funded through the Misophonia Research Fund on a yearly basis. Salaries follow the post-doctoral scale and are based on experience.
TERMS AND CONDITIONS OF EMPLOYMENT
Employment of the successful candidate is contingent upon the successful completion of a pre-employment criminal background check.
TO APPLY
Please apply online at https://hr.uconn.edu/jobs, Staff Positions, Search #499299 to upload a single PDF file containing:
All employees are subject to adherence to the State Code of Ethics which may be found at https://portal.ct.gov/Ethics/Statutes-and-Regulations.
All members of the University of Connecticut are expected to exhibit appreciation of, and contribute to, an inclusive, respectful, and diverse environment for the University community.
The University of Connecticut aspires to create a community built on collaboration and belonging and has actively sought to create an inclusive culture within the workforce. The success of the University is dependent on the willingness of our diverse employee and student populations to share their rich perspectives and backgrounds in a respectful manner. This makes it essential for each member of our community to feel secure and welcomed and to thoroughly understand and believe that their ideas are respected by all. We strongly respect each individual employee's unique experiences and perspectives and encourage all members of the community to do the same. All applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
The University of Connecticut is an AA/EEO Employer.
Advertised: Nov 04 2025 Eastern Standard Time
Applications close:
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Search #: 499299
Work type: Full-time
Location: UConn Storrs
Categories: Research, Postdoctoral Research Associates
JOB SUMMARY
The Physiological Acoustics Lab (http://escabilab.uconn.edu) at the University of Connecticut seeks applicants for a postdoctoral position in systems and computational neuroscience.
DUTIES AND RESPONSIBILITIES
We are seeking highly motivated and creative applicants who can lead a project on Misophonia, a psychological and behavioral disorder in which individuals experience adverse emotional reactions to specific sounds ("auditory triggers"). The broad project goal is to develop computational models of hearing and perception that are fitted to human perceptual measurements and that can be used to characterize and diagnose misophonia. The models will also be used to develop sound processing tools to remove and de-emphasize auditory triggers (e.g., with headphones) and improve participant outcomes. The project will use a variety of approaches, including human perceptual experiments, machine learning, digital signal processing, and computational models of hearing.
UConn has a vibrant neuroscience community, and there are opportunities for collaboration between departments, institutes, and Universities involved in the project. The primary appointment is in Biomedical Engineering and/or Electrical Engineering. The work will be conducted in collaboration with the Behavioral Neuroscience program in the Psychological Sciences department (Ian Stevenson), the Electrical and Computer Engineering/Biomedical Engineering departments at the University of Connecticut (Monty Escabí), and the Connecticut Institute for Brain and Cognitive Sciences.
MINIMUM QUALIFICATIONS
- A PhD in Neuroscience, Biomedical Engineering, Computational Neuroscience, or a related field is required.
- Experience with experimental design, data analysis, and/or modeling.
PREFERRED QUALIFICATIONS
- Previous experience, education, or general proven knowledge in hearing or speech and language sciences.
- Interdisciplinary research experience in computational and systems neuroscience with prior research experience in human behavior, animal behavior and/or brain physiology.
- A strong analytic background, particularly in modeling neural systems and analyzing large datasets.
- Experience with acoustic signal processing, sound recognition, and machine learning.
APPOINTMENT TERMS
This is a full-time, 12-month position funded through the Misophonia Research Fund on a yearly basis. Salaries follow the post-doctoral scale and are based on experience.
TERMS AND CONDITIONS OF EMPLOYMENT
Employment of the successful candidate is contingent upon the successful completion of a pre-employment criminal background check.
TO APPLY
Please apply online at https://hr.uconn.edu/jobs, Staff Positions, Search #499299 to upload a single PDF file containing:
- a resume (including past research experience and published work),
- a one-page statement of prior research experience,
- a one-page statement of future research interests and objectives, and
- the names and contact information of at least two individuals who can provide reference letters.
All employees are subject to adherence to the State Code of Ethics which may be found at https://portal.ct.gov/Ethics/Statutes-and-Regulations.
All members of the University of Connecticut are expected to exhibit appreciation of, and contribute to, an inclusive, respectful, and diverse environment for the University community.
The University of Connecticut aspires to create a community built on collaboration and belonging and has actively sought to create an inclusive culture within the workforce. The success of the University is dependent on the willingness of our diverse employee and student populations to share their rich perspectives and backgrounds in a respectful manner. This makes it essential for each member of our community to feel secure and welcomed and to thoroughly understand and believe that their ideas are respected by all. We strongly respect each individual employee's unique experiences and perspectives and encourage all members of the community to do the same. All applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
The University of Connecticut is an AA/EEO Employer.
Advertised: Nov 04 2025 Eastern Standard Time
Applications close:
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What University Of Connecticut employees say
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About University of Connecticut
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Industry
Colleges, universities, and professional schools
Company size
1,001 - 5,000 Employees
Headquarters location
Stamford, CT, US
Year founded
1881