Computational Chemist
Pacagen (pacagen.com) is disrupting consumer goods industries through biotechnology-
backed products. Our first products neutralize pet allergens in the air and on surfaces. We have excellent initial traction (growing 30% every month at >$2M/year revenue run rate in <5 months after launching). We are actively incubating new technologies in the allergy space.
We are venture-funded and backed by some of the best firms in the consumer space (led by Maveron) and founded by experienced and successful entrepreneurs who have built and sold nine-figure businesses before. We are seeking a proactive and highly-motivated individual to lead our efforts in discovering molecules that could change a consumer’s approach to allergies. As our Computational Chemist, you’ll work with the most cutting-edge frameworks in virtual molecular docking and machine learning. You’ll assist with in silico screening and the development of Pacagen’s products. The best candidate will have extensive experience in the computational drug discovery process.
You directly work with our co-founders to push the frontiers of consumer allergy health. This role is for someone who actively enjoys working in a fast-paced environment while taking on larger responsibilities within a fast-growing organization.
Responsibilities:
● Own a zero-to-one initiative to launch the best virtual screening pipeline for novel consumer allergy products.
● Lead development of our computational discovery platform for anti-allergen nanobodies and novel molecules.
● Keep up with state-of-the-art methods for predicting and optimizing protein-protein interactions, including AI/ML-based approaches.
● Develop high-quality code within a fast-paced environment.
● Continuously iterate with senior leadership about results, challenges, and solutions in an ever-changing business landscape.
Requirements:
● PhD in computational chemistry, computational biology, or related field.
○ Ideal: 1-3 years of industry work experience.
● Experience with computational chemistry tools and software, such as molecular dynamics software (LAMMPS, NAMD, CHARMM, GROMACS, AMBER), visualization tools (PyMol, Chimera), and querying data sources such as UniProt and the Protein Data Bank
● Experience developing and/or applying machine-learning (ML) based approaches to predicting protein structure and protein-protein interactions, such as AlphaFold/RoseTTAFold, geometric graph neural networks, ML model development in Keras/Jax/PyTorch/TensorFlow.
● Experience with in silico or de novo approaches to sequence-based and structure-based design of protein-binding proteins and molecule-binding proteins, including diffusion models, language models, and/or high-throughput virtual screening for hotspot prediction, docking, and binding optimization
● Ability to work independently and in a team.
● Track record of high-quality coding.
● Can communicate clearly and concisely.
● Thrives in a fast-paced environment.
● Can multitask and adhere to deadlines.
● Doesn’t take good enough for an answer - constantly trying to improve themselves to help their team win.
Why work with us?
We’re a fast-paced startup that is delivering life-changing products. We have a team that works hard to make sure that we can get those products into the hands of the people that need them most. Working at Pacagen will be an exciting growth opportunity for your career. You’ll get exposure to world-class partners, mentors, and innovative people from every field.
Why NOT work with us?
You’ll notice that the phrase “fast-paced” is in this job description multiple times. Building an amazing, profitable company in a few years is not easy. We aren’t here to pretend like it
is (believe us, we’ve done it before). Startups are hard and stressful. They are not meant for everyone. But on the flip-side, they can be extremely rewarding and enriching. The best performers get a career boost more drastic than anything they could imagine, but not everyone is fit for the job.
Location: New York, New York
Starting Date: Anytime