Bringing a single new drug to the market costs $2.9B and takes 15 years, with a high chance of failure. At GTN we combine machine learning and quantum physics, using our unique patent-pending technology, Generative Tensorial Networks, to efficiently access the full drug-like space of ca. 1060 dimensions, and to more accurately predict chemical activities. This has the potential to create substantial efficiencies in the whole drug development cycle which could have a huge positive impact on lives globally.
We are looking for an outstanding computational chemist with an adaptable and productive working style which would fit in a fast-moving biotech startup.
As part of the role you will:
· Help define the strategy and deliver the pipeline for FEP/TI augmentation of data.
· Help refine the machine learning model output in reference to docking.
· Work with the engineering team to define infrastructure and engineering needs for computational calculations.
· Incorporate ideas from the current literature approaches into structure based drug design.
· Rapidly gain a high level understanding of and assimilate other disciplines within the team including machine learning and quantum physics.
As part of an ambitious, fast-paced and interdisciplinary team working on tough but impactful challenges, you can expect to work in a collaborative and intellectually fulfilling environment, working on problems that really matter.
What we expect:
· Experience with protein and ligand structure-based model building.
· Experience with molecular dynamics and free energy perturbation calculations, ideally applied to pharma problems.
· A Ph.D. in a related field with some pharma/CRO/Biotech experience (will consider significant experience in lieu of a Ph.D.)
· Experience delivering results and problem solving in pharma programmes.
· An understanding of the drug discovery process.
· Experience in bioinformatics/cheminformatics ie. (docking, QSAR/homology model building, protein homologue building).
· A desire to work with on difficult problems that can have a real impact on the world.
For more information and to apply please click here.
Caltech is a world-renowned science and engineering institute that marshals some of the world’s brightest minds and most innovative tools to address fundamental scientific questions. We thrive on finding and cultivating talented people who are passionate about what they do. Join us and be a part of the diverse Caltech community.
The Theoretical and Computational Scientist will report to Garnet Chan. This is a term assignment lasting 12 months from the date of hire, with possibility for renewal. Additional or extended funding may result in extension of the original length of the assignment. The Theoretical and Computational Scientist will technically contribute to scientific research on electronic structure theory, and will contribute to the code development of the PySCF software package.
– Work on projects associated with molecular and condensed phase quantum chemistry.
– Develop new software and maintain existing software associated with the group, including but not limited to the PySCF package.
– Help organize internal group seminars and provide coding assistance to the group members.
– Perform other duties as assigned.
– PhD in Chemistry or Physics.
– 3 or more years of programming experience (C++, Fortran, Python).
– Basic knowledge of quantum chemistry.
– Unix or Linux experience.
– Good communication with collaborators.
– Advanced knowledge of quantum chemistry and condensed matter electronic structure.
– 5 or more years of programming experience (C++, Fortran, Python) developing large-scale quantum chemistry packages.
The Shirts research group in the Department of Chemical and Biological Engineering at University of Colorado Boulder is hiring a research associate to help develop guidelines, based on fundamental physical principles, by which short nonbiological heteropolymers with sequence specificity can fold into secondary structure elements. The candidate will also study what governs the relative stability between these allowed secondary structural elements. Initial studies will pave the way for more extensive and realistic modeling of the proposed heteropolymers, working with our experimental collaborators. The research effort is intended to build towards tools for designing human-engineered foldameric materials with a much larger range of properties and functions than occur in naturally occurring biological heteropolymers such as proteins. This position requires a Ph.D. in chemistry, chemical engineering, physics or a related field, and exceptionally strong skills in statistical mechanics and molecular simulation. Other potential (but not required) qualifications of interest include Python expertise and experience with protein design algorithms. Competitive candidates will have a track record of scientific success in graduate study, creative and innovative thinking, experience working on teams, excellent writing skills, and a strong publication record.
To apply for the job, visit https://cu.taleo.net/careersection/2/moresearch.ftl and search for job #13828. A direct link to the posting is: https://cu.taleo.net/careersection/2/jobdetail.ftl?job=13828&lang=en&sns_id=mailto#.WxqhPKQ7H5Y.mailto Note: the CU application requires a letter of recommendation, but that does not need to be uploaded initially; that can be uploaded as a confidential letter of recommendation later in the process by Prof. Shirts.
The Kasson laboratory is seeking a postdoctoral scholar to help further the development of the Gromacs molecular simulation package. We are seeking a postdoctoral scholar with strong software engineering skills to help build this widely-used scientific software package. This scholar will gain experience in and exposure to the broad base of Gromacs users and developers as well as skills in API design and parallel cloud-computing analytics.
Candidates must have a PhD in hand by the start date. Skills not only in C++ and Python programming but also version control and code review systems are essential. A track record of contributions to open-source software is required as well. Scientific background related to simulation science is required; competitive candidates will have a track record of scientific success in graduate study with a strong publication record. Successful candidates must also excel at both independent research and close collaboration in multi-site teams. Candidates will be evaluated on match for the position, research accomplishments, and research trajectory, in addition to other factors.
To apply, visit jobs.virginia.edu/applicants/Central?quickFind=85131. Complete a candidate profile online and attach a cover letter with statement of research interests, a CV with publication list and links to prior software contributions (Github, commit records for other software projects, etc.), and contact information for three references.
The University of Virginia is an equal opportunity and affirmative action employer. Women, minorities, veterans and persons with disabilities are particularly encouraged to apply.
The Complex Systems and Optimization Group in NREL’s Computational Science Center has an opening for a full-time postdoctoral researcher for machine learning to enable molecular and atomistic simulations of complex energy materials. In this position, the candidate will produce software and perform simulations that combine quantum mechanical calculations of electronic structure with classical and ab initio molecular dynamics and machine learning algorithms towards the overarching goal of developing transferable and chemically aware methods for simulating complex multi-scale systems on leadership class supercomputing resources. This research will develop code to automatically create and refine classical simulations using chemical information from large-scale DFT calculations. The initial applications will be in the areas of hybrid perovskite materials and covalent organic frameworks for solar energy conversion, catalysis and separation applications. As a member of the Computational Science Center, the postdoctoral researcher also will work with NREL’s supercomputing resources, with the opportunity to work on making software and methods useable in a high-performance computing context. For a full description, please see the link to NREL’s job web site.
Required Education, Experience, and Skills: Must be a recent PhD graduate within the last three years.
EEO Policy: NREL is dedicated to the principles of equal employment opportunity. NREL promotes a work environment that does not discriminate against workers or job applicants and prohibits unlawful discrimination on the basis of race, color, religion, sex, national origin, disability, age, marital status, ancestry, actual or perceived sexual orientation, or veteran status, including special disabled veterans.
The Center for Research Computing (CRC) in conjunction with the Department of Chemistry at the University of Pittsburgh invites applications for a Research Assistant Professor position (outside the tenure stream). The ideal candidate will have a strong background in electronic structure methods for finite and periodic systems as well as optimization and code development for HPC and GPU platforms. A PhD in chemistry, physics, materials science, or related area is required. Experience with machine learning would be a plus.
CRC is dedicated to supporting and facilitating computational-based research across the University. It serves as a catalyst for collaboration, education and outreach and provides consultation and research collaboration to faculty and students in a wide range of disciplines. Primary roles for this position include contributing to evolving the vision of the Center, and assisting faculty, postdocs, and students in effectively applying our advanced computing systems for deriving insights from their research. As teaching is integral to our mission, strong verbal and written communication skills are a requirement.
Application Process: If interested, please submit a CV and a cover letter to Wendy Janocha (firstname.lastname@example.org). The cover letter can be addressed to Ralph Roskies, Vice Chancellor for Research Computing, and should specifically address how your background, experience, and career goals align with the responsibilities of this position. The search will continue until the position is filled. Final appointment to this position will be contingent on receipt of three strong letters of recommendation on your behalf.
University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EEO/AA/M/F/Vets/Disabled