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Postdoctoral Fellow (Machine Learning and Data Science)

Lilu

Lilu

Software Engineering, Data Science
New York, NY, USA · Remote
Posted on Thursday, August 10, 2023

**PHD IS REQUIRED TO BE ELIGIBLE FOR THIS FELLOWSHIP*

At Lilu, we build technology to empower new moms. We’re currently working on an exciting project funded by the National Science Foundation that aims at building a state of the art, smart wearable device for new moms. This fellowship focuses on analyzing Lilu sensor data.
Learn more about us here: www.wearlilu.com.

RESEARCH OPPORTUNITY:

We’re building a product that will make a significant impact on breastfeeding mothers who experience difficulties producing milk or determining the volume of milk expressed during each session. While the benefits of breastfeeding throughout the first year of a baby’s life are widely accepted in the medical community, 60% of mothers do not succeed in sustained breastfeeding. The success or failure of breastfeeding is dependent upon a baby getting enough milk, and currently there is no objective method of determining the amount of milk a baby is receiving.

The device we’re building collects raw data that we can analyze to track breastfeeding-related activities. The next step is to analyze this data to help mothers overcome challenges in breastfeeding and avoid further complications like clogged ducts and/or mastitis. The depersonalized data collected from the bra will enable medical professionals and researchers to gain insights about human milk production volumes and factors influencing milk production and infant health.

The focus of this fellowship would be to analyze the data gathered from the Lilu sensors, understand it in the context of breastfeeding and lactation, and propose and build AI and ML tools to uncover insights for mothers.

DESIRED KNOWLEDGE:

Lilu is looking for a Postdoc that is proficient in researching, implementing and testing machine learning algorithms. Specifically, experience and interest in healthcare is preferred as well as a desire to contribute to building technology for typically underserved communities. Lilu envisions this hire to drive the entire lifecycle of the data flow: all the way from articulating the problem, to data collection, to combining data from different sources, data cleanup and preprocessing to proposing the model, feature engineering, model implementation and finally, clearly communicating results.

The ideal candidate has experience in applied data science, is proficient in python, possesses a strong statistical and mathematical background and is able to think critically and creatively to thrive in a fast paced start-up environment.

ABOUT THE INNOVATIVE POSTDOCTORAL ENTREPRENEURIAL RESEARCH FELLOWSHIP

About NSF I-PERF:
This is your opportunity to use your skills at a high-tech start-up and gain experience in industry. Funded by the National Science Foundation (NSF), the Innovative Postdoctoral Entrepreneurial Research Fellowship (I-PERF) recruits, trains, and funds early-career Science and Engineering doctoral degree recipients to participate in innovative research at an NSF-funded start-up.

Compensation & Benefits:
I-PERF fellows receive an annual stipend of $78,000 per year, optional individual health and life insurance benefits, relocation assistance, a professional conference travel allowance, and scripted professional development training funded by the NSF.

Applicant Eligibility:
Applicants must hold an earned doctoral degree in an NSF-supported STEM discipline from a recognized Ph.D. granting institution. They must have earned this degree within 7 years of application to I-PERF and be a U.S. citizen, national, or permanent resident at the time of application. Emphasis will be placed on members of socio-economic disadvantaged groups, members of underrepresented groups in science and engineering, persons with disabilities, veterans of the U.S. Armed Forces, and first generation college graduates. For more information, visit: https://iperf.asee.org/

TO APPLY

Create an applicant account at this link: https://iperfapp.asee.org/
Once your application is complete (under Applicant Profile), select Research Opportunities, search for Lilu, and connect with us!