Principal Scientist - Computational Protein Design
Principal Scientist - Computational Protein Design
Posted on :
22-02-2025
Employer Active
1 Vacancy
The job posting is outdated and position may be filled
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Share
Send me jobs like this
Job Alert
You will be updated with latest job alerts via emailValid email field required
Send jobs
Job Description
Job Title: Principal Scientist Computational Protein Design
Job Location: Hyderabad Telangana India
Job Location Type: Hybrid
Job Contract Type: Parttime
Job Seniority Level: MidSenior level
PopVax is an Indian fullstack biotechnology company developing novel mRNA vaccines and therapeutics using computational protein design. Our first vaccine is a nextgeneration COVID19 booster which will enter a firstinhuman Phase I clinical trial in the U.S. early this year. This vaccine is intended to broaden protection against both current and predicted future SARSCoV2 variants reducing the possibility of a new mutation in the virus suddenly causing another massive wave of infection. We have a preclinical pipeline of 6 additional novel vaccine candidates built on our mRNALNP platform that we will be taking into clinical trials over the next few years. Our work to date has been funded primarily via project agreements totalling 10 million USD with the Bill & Melinda Gates Foundation and Vitalik Buterin's public health & biosecurity organisation Balvi.
Our antigen design strategy for our current vaccine candidate and our intended strategy for future vaccines extensively uses a wide variety of protein design and engineering techniques from oldschool brute force mutation guided by free energy approximations and molecular dynamics simulations to MLbased approaches like constrained hallucination inpainting and diffusion for de novo structure generation and protein language models for sequence embedding and optimization.
We have seen up close that there are incredible capabilities in computational protein design just waiting to be unlocked that will make possible the focusing and finetuning of immune responses to enable an entirely new class of vaccines and therapeutics. We have already seen some impressive results from our work – early versions of our first vaccine candidate perform 10120x better than existing mRNA vaccines in pseudovirus neutralization assays against key COVID19 variants – and our results improve every week as we iterate in a tight in silico to in vivo loop far more rapidly than was ever possible in the past.
In doing so we stand on the shoulders of the good folks at DeepMind (AlphaFold) the Institute for Protein Design at the University of Washington (Rosetta/RFDesign) the AlQuraishi Lab at Columbia the Possu Huang Lab at Stanford the OpenFold consortium and many others who have pioneered these techniques over the last decade and with particularly breathtaking speed over the last couple of years.
We want to employ these approaches as well as new ones we invent in service of an ambitious agenda – the rapid design and validation of broadlyprotective vaccines against all key families of pandemic potential pathogens which we see as an essential tool to preempt the emergence of new zoonotic pathogens and if we get this right perhaps even prevent not one but many future pandemics from happening in the first place.
We seek to do this while ensuring that the benefits our work brings are made available to the entire global population as soon as possible – it’s right in the name Populationscale Vaxccines – rather than being unevenly distributed based on wealth and geography as many of today’s great medical advances unfortunately are.
We’re looking for a small number of exceptionally competent and insatiably curious computational protein designers to join us on our mission. To qualify for this position a candidate must have used a variety of computational tools to design or engineer proteins and the ideal candidate will have familiarity with SOTA machine learning methods in the field. They must be able to write code at a level sufficient to write and train their own model implementations as well as customize existing models for our needs though they need not be expert software engineers or machine learning scaling specialists. We will look to pair our protein designers with staff software engineers and machine learning scientists to accelerate work where necessary.
We intend to allow for a relatively open culture of publication of both methods (via academic papers preprints and blog posts) as well as (where feasible) code and model weights. We also want to give individuals hired in this position the ability to pursue a research agenda independent of shortterm company goals for some portion of their working hours and will be setting up support mechanisms for this kind of work where possible. For candidates from academia who would like to keep a foot in that world we have premier academic institute partners with whom we may be able to negotiate a parttime appointment (for sufficiently qualified candidates).
While we will always prefer candidates who are able to work on site at our Hyderabad lab we are willing to consider exceptionally qualified remote work candidates for this position supplemented with site visits to Hyderabad.
Join us!
P.S. – want to apply but worried you don't quite meet the requirements If you believe you have enough background knowledge to quickly get up to speed feel free to apply and explain this in the relevant experience field of the application.
Our antigen design strategy for our current vaccine candidate and our intended strategy for future vaccines extensively uses a wide variety of protein design and engineering techniques from oldschool brute force mutation guided by free energy approximations and molecular dynamics simulations to MLbased approaches like constrained hallucination inpainting and diffusion for de novo structure generation and protein language models for sequence embedding and optimization.
We have seen up close that there are incredible capabilities in computational protein design just waiting to be unlocked that will make possible the focusing and finetuning of immune responses to enable an entirely new class of vaccines and therapeutics. We have already seen some impressive results from our work – early versions of our first vaccine candidate perform 10120x better than existing mRNA vaccines in pseudovirus neutralization assays against key COVID19 variants – and our results improve every week as we iterate in a tight in silico to in vivo loop far more rapidly than was ever possible in the past.
In doing so we stand on the shoulders of the good folks at DeepMind (AlphaFold) the Institute for Protein Design at the University of Washington (Rosetta/RFDesign) the AlQuraishi Lab at Columbia the Possu Huang Lab at Stanford the OpenFold consortium and many others who have pioneered these techniques over the last decade and with particularly breathtaking speed over the last couple of years.
We want to employ these approaches as well as new ones we invent in service of an ambitious agenda – the rapid design and validation of broadlyprotective vaccines against all key families of pandemic potential pathogens which we see as an essential tool to preempt the emergence of new zoonotic pathogens and if we get this right perhaps even prevent not one but many future pandemics from happening in the first place.
We seek to do this while ensuring that the benefits our work brings are made available to the entire global population as soon as possible – it’s right in the name Populationscale Vaxccines – rather than being unevenly distributed based on wealth and geography as many of today’s great medical advances unfortunately are.
We’re looking for a small number of exceptionally competent and insatiably curious computational protein designers to join us on our mission. To qualify for this position a candidate must have used a variety of computational tools to design or engineer proteins and the ideal candidate will have familiarity with SOTA machine learning methods in the field. They must be able to write code at a level sufficient to write and train their own model implementations as well as customize existing models for our needs though they need not be expert software engineers or machine learning scaling specialists. We will look to pair our protein designers with staff software engineers and machine learning scientists to accelerate work where necessary.
We intend to allow for a relatively open culture of publication of both methods (via academic papers preprints and blog posts) as well as (where feasible) code and model weights. We also want to give individuals hired in this position the ability to pursue a research agenda independent of shortterm company goals for some portion of their working hours and will be setting up support mechanisms for this kind of work where possible. For candidates from academia who would like to keep a foot in that world we have premier academic institute partners with whom we may be able to negotiate a parttime appointment (for sufficiently qualified candidates).
While we will always prefer candidates who are able to work on site at our Hyderabad lab we are willing to consider exceptionally qualified remote work candidates for this position supplemented with site visits to Hyderabad.
Join us!
P.S. – want to apply but worried you don't quite meet the requirements If you believe you have enough background knowledge to quickly get up to speed feel free to apply and explain this in the relevant experience field of the application.
/jobs/view/6499e62a6308c2c8aa0ed0b49cac9c1a
Employment Type
Full Time
Key Skills
Report This Job
Disclaimer: Drjobpro.com is only a platform that connects job seekers and employers. Applicants are advised to conduct their own independent research into the credentials of the prospective employer.We always make certain that our clients do not endorse any request for money payments, thus we advise against sharing any personal or bank-related information with any third party. If you suspect fraud or malpractice, please contact us via contact us page.
