Harmonic Discovery

We engineer drugs with targeted polypharmacology

Scientist, Cheminformatics at Harmonic Discovery

Location
Remote
Job Type
Full-time
Experience
Any (new grads ok)
Connect directly with founders of the best YC-funded startups.
Apply to role ›
Jason Lee
Jason Lee
Founder

About the role

About Us

Based in NYC, Harmonic Discovery is a venture-backed biotechnology company leveraging biology, medicinal chemistry and machine learning to create a new generation of multi-target kinase inhibitors for oncology and autoimmune disorders. At Harmonic Discovery, we are building a multifaceted and incredible team of biologists, chemists and machine learning engineers to solve the problem of designing drugs with targeted polypharmacology.

We look for passionate innovators, radical thinkers and collaborative builders. It’s time to integrate our understanding of biology and chemistry with better AI to make superior cures that make a difference in people’s lives.

Harmonic Discovery is backed by top tier venture firms and is a member of Johnson & Johnson’s accelerator – JLABS @ NYC. We are also backed by YCombinator.

Job Description

Harmonic Discovery is looking for a cheminformatics scientist to help build our computational chemistry platform. We are recruiting exceptional scientists to perform virtual screening, engineer molecular descriptors, manage and populate our internal chemical databases, analyze various small molecule datasets, as well as train machine learning models on chemical information. You will also be strongly involved in the design and development of the Harmonic Discovery Cheminformatics Platform.

Harmonic Discovery is committed to a multicultural environment and strongly encourages applications from women and underrepresented minorities.

QUALIFICATIONS

• PhD in computational chemistry or a similar field. Exceptional MS candidates will be considered.

• Knowledge of chemistry, data analytics, statistics, and small molecule drug discovery development process.

• Enthusiastic about application of computational methods to drug discovery.

• Strong strategic, scientific and technical leadership.

• Strong communication skills.

• Collaborative, team-oriented mindset.

REQUIRED SKILLS

• Strong Python programming skills.

• Experience with Python libraries such as matplotlib, scikitlearn, numpy, etc.

• Experience with cheminformatics toolkits, such as RDkit, MarvinSketch, JChem, etc.

• Experience with virtual screening and docking software such as Vina, MOE, OpenEeye, Schrodinger.

• Experience with fingerprinting and molecular descriptors.

• Experience in bash and shell scripting.

PREFERRED SKILLS

• Experience with matched molecular pair database.

• Experience with deep learning platforms, such as TensorFlow, H2Oo.ai, and PyTtorch.

• Experience with generative machine learning models for chemistry.

• Experience with graph-based modeling for chemical structures.

• Experience with (quantitative) structure activity relationship modeling and chemical clustering techniques.

WHAT WE OFFER

• Highly competitive salary, benefits (healthcare, 401k matching, etc.) and stock options

• Significant responsibilities with potential for growth.

• Work from anywhere! Come by the office if you feel like it, or don’t. Your call. Feel free to work from anywhere in the US if you have a stable internet connection and can sync your calendar’s time zone with the team’s.

• You will work closely with the entire team, from the scientists to the CEO.

• No busy work here, you’ll work on projects that have an immediate and obvious impact to the company.

Harmonic Discovery is an equal opportunity employer. Harmonic Discovery recruits and employs regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law.

Why you should join Harmonic Discovery

We are a drug discovery company developing a new generation of therapeutics that embrace the complexity of disease. Currently available approaches for creating drugs work on the principal of finding one drug-one protein 'magic bullets'. However, diseases such as cancer and autoimmunity are often the result of several dysregulated proteins across many distinct biological pathways.

We are building a computational-experimental platform to design therapeutics that can target several disease-causing proteins at once. By designing multi-specific drugs, we are able to create therapeutics that are more efficacious and safer than existing medicines.