Chimico Computazionale
We are seeking an experienced and highly motivated Computational Chemist to support and drive small-molecule drug discovery programs. The successful candidate will combine strong CADD expertise, structural biology knowledge, and practical experience with AI/ML-enabled molecular design to identify and optimize high-quality chemical starting points. The role requires a solid foundation in computational chemistry and CADD, together with the ability to integrate structural, chemical and biological data into actionable hypotheses and compound-design strategies.The successful candidate will join our group of Hit and Lead Discovery Group based in Torre Annunziata – Naples.
Di seguito troverà tutto ciò che deve sapere su questa possibilità e sui requisiti richiesti ai candidati.
Key Responsibilities
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- Support hit identification, hit-to-lead and lead optimization activities across different drug discovery programs.
- Design and apply structure-based and ligand-based drug design strategies to support compound identification and optimization.
- Plan and execute virtual screening and compound prioritization activities, using appropriate approaches such as molecular docking, similarity searching, pharmacophore modelling and QSAR modeling.
- Analyze and integrate chemical, structural and biological data to interpret structure-activity relationships and guide compound design and prioritization.
- Apply appropriate computational methods, including molecular modelling and molecular dynamics, to address project-specific scientific questions.
- Develop and implement reproducible computational workflows for data processing, analysis and visualization.
- Work closely with medicinal chemists,
biologists and other project team members to support data-driven decision-making.
- Clearly communicate computational results, recommendations and project updates to internal teams and, when appropriate, external partners and clients.
Qualifications & Skills
-
- Ph.D. in Computational Chemistry, Chemistry, Structural Biology, Biophysics, Bioinformatics, or a closely related discipline.
- At least 2-3 years of relevant experience in computational chemistry applied to drug discovery, preferably in an industrial, biotech, pharmaceutical or CRO environment.
- Good knowledge and practical experience in structure-based and ligand-based drug design, virtual screening, molecular docking and SAR interpretation; in binding-site analysis, FEP calculations, similarity search, pharmacophore modeling, and QSAR models
- Experience working with protein structures and protein-ligand complexes, including experimental or predicted structural models.
- Hands‑on experience with one or more commonly used molecular modelling platforms and tools, such as preferably the Schrödinger suite and REINVENT.
- Ability to work with chemical and biological datasets and to develop or use reproducible computational workflows.
- Ability to implement scalable algorithms and computational workflows for the analysis of large-scale molecular datasets, including clustering, similarity analysis,
dimensionality reduction and chemical space exploration.
- Familiarity with Python, R or other programming/scripting languages used for scientific data analysis.
- Ability to work effectively in a multidisciplinary drug discovery environment.
- Fluent English, written and spoken, with good scientific communication skills.
Nice to Have
-
- AI/ML approaches applied to molecular design and drug discovery, including generative approaches, property prediction or compound prioritization.
- Advanced computational methods such as free-energy calculations, MM-GBSA, FEP, QM calculations or enhanced sampling.
- ADMET and physicochemical property prediction.
- Fragment-based drug discovery, covalent inhibitors or targeted protein degradation.
- Experience with KNIME, ChemAxon, CDD Vault and Dotmatics.
- Hands‑on experience with MOE, OpenEye, GROMACS, and AMBER or equivalent.
- Previous exposure to client-facing projects, CRO environments or integrated drug discovery programs.
- Scientific publications, patents or presentations demonstrating contributions to computational drug discovery.
Personal Attributes
-
- Strong scientific curiosity and problem-solving skills.
- A rigorous and data-driven approach.
- The ability to work collaboratively in multidisciplinary teams.
- Good interpersonal and communication skills.
- Enthusiasm for applying and expanding computational approaches to real drug discovery challenges. xysqume
Axxam is an equal opportunity employer
Axxam offers a stimulating work environment and a competitive salary.
Axxam S.p.A.
Openzone - via Meucci 3 - 20091 Bresso (Milano, Italy)
Fax – J-18808-Ljbffr
Di seguito troverà tutto ciò che deve sapere su questa possibilità e sui requisiti richiesti ai candidati.
Key Responsibilities
-
- Support hit identification, hit-to-lead and lead optimization activities across different drug discovery programs.
- Design and apply structure-based and ligand-based drug design strategies to support compound identification and optimization.
- Plan and execute virtual screening and compound prioritization activities, using appropriate approaches such as molecular docking, similarity searching, pharmacophore modelling and QSAR modeling.
- Analyze and integrate chemical, structural and biological data to interpret structure-activity relationships and guide compound design and prioritization.
- Apply appropriate computational methods, including molecular modelling and molecular dynamics, to address project-specific scientific questions.
- Develop and implement reproducible computational workflows for data processing, analysis and visualization.
- Work closely with medicinal chemists,
biologists and other project team members to support data-driven decision-making.
- Clearly communicate computational results, recommendations and project updates to internal teams and, when appropriate, external partners and clients.
Qualifications & Skills
-
- Ph.D. in Computational Chemistry, Chemistry, Structural Biology, Biophysics, Bioinformatics, or a closely related discipline.
- At least 2-3 years of relevant experience in computational chemistry applied to drug discovery, preferably in an industrial, biotech, pharmaceutical or CRO environment.
- Good knowledge and practical experience in structure-based and ligand-based drug design, virtual screening, molecular docking and SAR interpretation; in binding-site analysis, FEP calculations, similarity search, pharmacophore modeling, and QSAR models
- Experience working with protein structures and protein-ligand complexes, including experimental or predicted structural models.
- Hands‑on experience with one or more commonly used molecular modelling platforms and tools, such as preferably the Schrödinger suite and REINVENT.
- Ability to work with chemical and biological datasets and to develop or use reproducible computational workflows.
- Ability to implement scalable algorithms and computational workflows for the analysis of large-scale molecular datasets, including clustering, similarity analysis,
dimensionality reduction and chemical space exploration.
- Familiarity with Python, R or other programming/scripting languages used for scientific data analysis.
- Ability to work effectively in a multidisciplinary drug discovery environment.
- Fluent English, written and spoken, with good scientific communication skills.
Nice to Have
-
- AI/ML approaches applied to molecular design and drug discovery, including generative approaches, property prediction or compound prioritization.
- Advanced computational methods such as free-energy calculations, MM-GBSA, FEP, QM calculations or enhanced sampling.
- ADMET and physicochemical property prediction.
- Fragment-based drug discovery, covalent inhibitors or targeted protein degradation.
- Experience with KNIME, ChemAxon, CDD Vault and Dotmatics.
- Hands‑on experience with MOE, OpenEye, GROMACS, and AMBER or equivalent.
- Previous exposure to client-facing projects, CRO environments or integrated drug discovery programs.
- Scientific publications, patents or presentations demonstrating contributions to computational drug discovery.
Personal Attributes
-
- Strong scientific curiosity and problem-solving skills.
- A rigorous and data-driven approach.
- The ability to work collaboratively in multidisciplinary teams.
- Good interpersonal and communication skills.
- Enthusiasm for applying and expanding computational approaches to real drug discovery challenges. xysqume
Axxam is an equal opportunity employer
Axxam offers a stimulating work environment and a competitive salary.
Axxam S.p.A.
Openzone - via Meucci 3 - 20091 Bresso (Milano, Italy)
Fax – J-18808-Ljbffr