Model Development and Improvement:
– Conduct research on protein de novo prediction and protein design/engineering models, with an emphasis on the development of novel de novo prediction or diffusion-based protein design models or the enhancement of existing open-source models such as OpenFold and Genie.
– Develop and implement algorithms to improve the accuracy and efficiency of protein structure predictions and protein design, including finding novel routes to score predictions to guide selection for experimental research.
– Collaborate with cross-functional teams to integrate model improvements into PUXANO’s experimental validation platform, including CryoEM image processing workflows.
Research and Innovation
– Stay abreast of the latest scientific literature and advancements in protein prediction, protein design and engineering, and cryoEM image processing.
– Propose and lead innovative ML/DL research projects within PUXANO and in collaboration with external teams aimed at advancing PUXANO’s Gene-to-Structure or Design-to-Structure capabilities and offerings.
Collaboration and Communication
– Work collaboratively with internal and external stakeholders, including Pharma and Biotech partners.
– Communicate complex technical concepts effectively to both technical and non-technical audiences.
– Contribute to grant writing and funding proposals to support ongoing research initiatives.
– Ph.D. in Computer Science, Physics, Computational Biology, Bioinformatics, Structural Biology, or a related field.
– Strong background in machine learning and deep learning techniques, particularly in the context of protein science.
– Experience with protein structure prediction and computational modeling.
– Experience in using HPC resources and training models on GPU clusters (e.g. EuroHPC).
– Proficiency in programming languages such as Python, and deep learning frameworks like Tensorflow, Pytorch, and other related tools.
– Excellent problem-solving skills and a track record of innovative research.
– Strong communication skills and the ability to work collaboratively in a fast-paced, interdisciplinary environment.
– Familiarity with cryo-electron microscopy (cryoEM).
– Knowledge of structural bioinformatics and molecular dynamics simulations.
– Previous experience in the Pharma or Biotech industry.
Interested candidates should submit a resume, including a GitHub link showcasing computational work, a cover letter, and contact information for three references (including technical references for questions) to careers@puxano.com. Candidates without demonstrable expertise in ML/DL through GitHub or contributions to ML/DL scientific papers will not be considered.
PUXANO is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Application Deadline: November 2024
Join PUXANO and be a part of a pioneering team that’s shaping the future of protein design and structure-based research!
