About Nextmol
Nextmol is a spin-off company of the
Barcelona Supercomputing Center, offering advanced services in
Molecular Simulation
and
Artificial Intelligence
applied to chemistry. We are developing a cutting-edge software platform designed to accelerate the design and discovery of new chemical compounds. Our mission is to support the chemical industry in its green and digital transition, by enabling a faster development of sustainable chemicals to achieve circular economy and climate neutrality, comply with regulatory framework, and meet current consumer demands.
Job Description
We are seeking an
R&D; Engineer
with a strong background in
computational chemistry
and a passion for integrating
molecular modeling
with
data-driven approaches. This position focuses on
applied research, where you will design, develop, and validate cutting-edge tools for
molecular design and characterization. Beyond research, you will help transform these tools into
production-ready solutions
that accelerate the discovery and design of new materials and chemicals for real-world applications.
We expect candidates to be comfortable navigating
interdisciplinary challenges, collaborating with chemists, physicists, and data scientists to bridge molecular modeling and data science, solve complex scientific problems, and deliver innovative solutions.
Key Responsibilities
Molecular modeling:
Use molecular modeling methods, particularly molecular dynamics (MD), to characterize molecular systems and produce high-quality datasets.
Machine Learning:
Develop, train, and optimize machine learning models for chemical property prediction and structure–property relationship analysis.
Chemical Space Exploration:
Apply advanced algorithms for chemical space exploration, including generation of molecules and screening for desired properties.
Integration and screening
:
Connect data-driven approaches with molecular simulations to accelerate property prediction and material discovery via high-throughput screening.
Scalability & Deployment:
Contribute to transitioning research prototypes into scalable, production-ready solutions for industrial applications.
Documentation & Reproducibility
: Ensure proper documentation of models, workflows, and datasets for reproducibility and compliance with best practices.
Qualifications
Technical Qualifications
Education
: PhD in Chemistry, Physics, or a related STEM discipline.
Molecular Modeling
: Hands-on experience in computational modeling, particularly molecular dynamics using tools such as GROMACS or LAMMPS.
Machine Learning:
Proven experience in machine learning theory and applications for chemistry, e.G. property prediction and structure-activity relationships.
Generative Methods
: Expertise in chemical space exploration and molecule generation.
Domain Knowledge:
Experience with polymers and surfactants (concerning both simulation and data-driven approaches) is highly valued, but not strictly required.
Programming Skills
: Proficiency in Python and common cheminformatics and ML frameworks (e.G., RDKit, Scikit-learn, MDAnalysis), with experience using Git.
Scientific Computing
: Familiarity with scientific computing and numerical methods, and HPC computing environments for large-scale simulations and model training.
Soft Skills & Professional Attributes
Problem-Solving
: Ability to learn new topics quickly and solve complex problems.
Engagement
: Motivation to meet project deadlines and promptly address customers’ needs.
Adaptability
: Capacity to adjust to evolving project needs and dynamic research environments.
Collaboration
: Effective team player with experience working in interdisciplinary environments.
Communication
: High level of English, both written and oral;
good presentationskills.
Why Join Us?
Innovation
: Contribute to cutting-edge projects at the intersection of AI and molecular science.
Impact
: Work on impactful industrial applications with real-world relevance.
Growth & Culture
: Join a dynamic, growing company with a collaborative team that values innovation, continuous learning, and personal development.
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