Research Engineer/Scientist, Machine Learning

AreteX Engineering – New York, NY

AreteX Engineering, a medical technology startup company accelerating the use of information technology in healthcare, has an immediate opening for a Research Engineer/Scientist 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 company has received grants from the Department of Defense and the National Science Foundation. 

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.

Minimum Requirements:

• MS or 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.

Responsibilities

• Collaborate with a team of machine learning, control engineering, and signal processing researchers.
• Provide technical expertise to address supervised and unsupervised learning problems in an applied research environment.
• Develop and deploy modern machine learning and statistical methods (CART and Random Forests, deep learning, clustering and classification algorithms, Bayesian models, neural networks, support vector machines, and probabilistic graphical models) for finding patterns and models from physiological data.

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.

Send your cover letter and CV to info@aretexeng.com.