Research Opportunities

AreteX Engineering - Signal Processing and Machine Learning

SBIR Award Title

Multi-Modality Agittation and Sedation Assessment for patients in ICU

SBIR Award Abstract

This Small Business Innovation Research Phase II project is concerned with developing a multi-modality agitation and sedation assessment system for patients in the intensive care unit (ICU). Specifically, we propose to use machine learning to integrate data from multiple sensing modalities to identify cases of undersedation and oversedation. Current clinical practice in patient critical care requires the nursing staff to assess the patient’s agitation and sedation state and provide sedatives to ameliorate the patient’s ag... more

Research Opportunity

Signal Processing and Machine Learning


137 Varick St.
2nd Floor
New York


Principal Investigator


AreteX Engineering, a medical technology startup company accelerating the use of information technology in healthcare, has an immediate opening for a NSF-sponsored Postdoctoral Fellow with a competitive salary in its office located in New York City, SoHo district. AreteX is a former resident of the Harvard Innovation Lab (ilab) and a current resident of the NYU Incubator.

The position involves developing machine learning algorithms for innovative biomedical technologies involving physiological signal processing and big data. We are looking for a self-motivated, highly talented individual with an excellent background in machine learning (statistical learning theory). The successful candidate will work closely with a team of physicians, nurses, engineers, and scientists in designing new clinical decision support systems.

Candidates with experience in the analysis of experimental data derived from---but not limited to---auditory/visual/cross-sensory psychophysical, EEG, ECG, and galvanic-skin conductance, data would be given a higher priority.

Desired Knowledge

Minimum Requirements:

PhD in computer science, electrical engineering, biomedical engineering, applied mathematics, or a similar discipline.
Expertise and innovation in methods, theory, and application of machine learning and data mining with a broad understanding of methodological approaches and proficiency in practice.
Expert abilities to work with new data sets regardless of prior exposure to current topic.
Strong interest in research and learning new technologies.
Proficient at writing technical papers/reports/presentations.
Experience with Python.
Familiarity with large data sets, cloud-based development and deployment, open source practices and frameworks is a plus.
Applicants must be U.S. citizens, U.S. nationals or U.S. permanent residents.
Applicant must have received a Ph.D. degree in the past 7 years.
Applicants must not have received a prior postdoctoral fellowship in a corporate laboratory for a term of more than six months.

Preferred Qualifications:

Prior expertise and exposure using non-invasive human physiological measures such as EEG, ECG, galvanic-skin conductance, or other categorically similar methodologies.
Prior experience in feature extraction from physiological signals.
Experience working with quantitative methods of neural data analysis.
Experience with speech, audio, or video technologies.