Noah Lorincz: Email & Phone Number

Opt-Out

Research Scientist, Statistical Genetics at Deep Genomics|United States

Position:

Research Scientist, Statistical Genetics at Deep Genomics

Location:

United States

View Noah Lorincz's Email

Up to 10 free lookups. No credit card required.

Last updated: 2026-06-10

Updated: 2026-06-10

Found email addresses for Noah Lorincz:

Business emails:

n**********z@deepgenomics.com

Personal emails:

n*************i@gmail.com

Found phones for Noah Lorincz:

+1-909-***-**25,

+1-909-***-**62,

+1-870-***-**63

A different Noah Lorincz?

Work Experience 3 years

Research Scientist, Statistical Genetics at Deep Genomics

Aug 2025 - Current

Postdoctoral Fellow at Cleveland Clinic

Feb 2024 - Aug 2025

Adjunct Professor of Biostatistics at Baldwin Wallace University

Feb 2024 - May 2024

Statistical Consultant at University Hospitals

Sep 2023 - Feb 2024

Statistical Consultant at Cancer Support Community Washington DC

Jul 2023 - Feb 2024

Statistical Consultant at University Hospitals

May 2023 - Jun 2023

Noah Lorincz started working in 2023, then the employee has changed 4 companies and 3 jobs. On average, Noah Lorincz works for one company for 8 months.

Their professional focus is Analytical Skills, Analytics, and Bioinformatics across 3 core areas.

Education

Doctor of Philosophy - PhD at Case Western Reserve University School of Medicine

MSc at King's College London

Bachelor of Arts - BA at Ohio University

Frequently Asked Questions

What is Noah Lorincz's email address?

SignalHire found verified email addresses for Noah Lorincz, both business and personal. Their business email is n**********z@deepgenomics.com, and personal emails include n*************i@gmail.com.

What is Noah Lorincz's phone number?

SignalHire found multiple verified phone numbers for Noah Lorincz: +1-909-***-**25, +1-909-***-**62, and +1-870-***-**63.

How do I contact Noah Lorincz at Deep Genomics?

You can reach Noah Lorincz through SignalHire by unlocking their verified email and direct phone number (free signup, no credit card needed). SignalHire is the fastest route if you need their contact details immediately.

What is Noah Lorincz's professional background?

Noah Lorincz has 3 years of professional experience. They have held roles including Postdoctoral Fellow, Adjunct Professor of Biostatistics, and Statistical Consultant at companies such as Cleveland Clinic, Baldwin Wallace University, and University Hospitals. Their education includes Doctor of Philosophy - PhD from Case Western Reserve University School of Medicine, and MSc from King's College London.

Is Noah Lorincz's contact information up to date?

Yes. Noah Lorincz's SignalHire profile was last updated on 10 June 2026, reflecting their current position as Research Scientist, Statistical Genetics at Deep Genomics in Toronto, Canada.

Other employees at Deep Genomics

Name

Company

Position

William Kelly

Deep Genomics

Laboratory Operations Associate Intern

Get contacts

Alexander Puerta

Deep Genomics

Software Engineer

Get contacts

Monika Kowalczyk

Deep Genomics

VP, Platform Technologies

Get contacts

Michael Slobodyanyuk

Deep Genomics

Data Scientist III

Get contacts

Yingxin

Deep Genomics

Senior Machine Learning Scientist

Get contacts

Eric Lee

Deep Genomics

Senior Financial Manager

Get contacts

Maggie Hong

Deep Genomics

Accounting Associate

Get contacts

Jason Wang

Deep Genomics

Software Engineer Intern

Get contacts

Siqi Zhao

Deep Genomics

Staff Machine Learning Scientist

Get contacts

Scott Findlay

Deep Genomics

Principal Scientist

Get contacts

See more profiles

Data Privacy

GDPR COMPLIANT

SignalHire complies with the General Data Protection Regulation (GDPR). SignalHire follows GDPR requirements, including but not limited to rights of data subjects to access, correct, or delete their personal information and supports the right to be forgotten.

CCPA COMPLIANT

SignalHire is CCPA-compliant and provides California residents the right to know, access, opt out, and request deletion of their personal data.