Associate Scientific Manager - Structural Biologist (PhD/Masters)
- Innoplexus
- 3 - 8 years
- Pune
- 1 month ago
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Job Description
****Please Note: Only candidates whose qualifications closely match the job description requirements will be contacted for the next stage of the recruitment process.*****
Key Responsibilities
1. Scientific Program Coordination (Computational & AI-Focused)
- Manage multi-disciplinary discovery initiatives that span protein engineering, target assessment, sequence-level modeling, generative molecule design, and multi-omics interpretation.
- Assist in defining project scopes, scientific milestones, and computational deliverables.
- Track progress across ML modeling, bioinformatics analyses, structural modeling cycles, and insight-generation workflows.
- Ensure scientific alignment across computational biology, cheminformatics, ML engineering, and platformdevelopment teams.
2. Protein Engineering & Structural Biology Support
- Coordinate computational strategies related to:
- protein sequence modeling and mutational scanning
- structure prediction (AlphaFold, ESMFold, Rosetta-based workflows)
- binding interface characterization and proteinligand or proteinprotein interactions
- stability/solubility prediction, developability assessments, and variant prioritization
- Review structural models, annotated residue-level insights, and design outputs generated by ML/AIplatforms.
- Integrate sequence- and structure-based computational results into program-level decision-making.
3. Multi-Omics & Bioinformatics Workflow Management
- Collaborate with computational biologists to design and support analyses involving transcriptomics,proteomics, single-cell data, and genome-wide datasets.
- Aid in selection and interpretation of:
- differential expression analyses
- pathway enrichment and network biology modeling
- biomarker discovery and target prioritization from omics datasets
- Organize pipelines for integrating omics-derived insights with AI predictions, structural features, and medicinal chemistry landscapes.
4. Data Integration & ML Problem Formulation
- Translate biological/scientific questions into machine learning tasks such as:
- protein fitness prediction
- generative sequence design
- ligandtarget affinity prediction
- ADMET or MoA modeling
- large-scale virtual screening
- Collaborate with ML engineers on dataset preparation, feature construction, labeling strategies, and model evaluation.
- Review outputs from predictive models and convert them into actionable insights for discovery teams.
5. Computational Workflow Development & Documentation
- Maintain structured, reproducible workflows across structural modeling, omics analysis, genetic variant scoring, and ML-driven design loops.
- Evaluate and help standardize emerging computational tools, databases, and algorithms relevant to protein science, bioinformatics, and ML.
- Develop and maintain internal documentation, pathway diagrams, decision frameworks, and best-practice guidelines.
6. Scientific Communication & Cross-Functional Liaison
- Prepare clear, data-rich scientific briefs, platform feature requests, white papers, and internal strategy documents.
- Present computational insights to scientific leadership, domain experts, and cross-functional stakeholders.
- Support manuscripts, conference presentations, grant applications, and external scientific communication.
Required Qualifications
Educational Background
- Masters/PhD in Computational Biology, Bioinformatics, Protein Engineering, Structural Biology, Systems
Biology, Computational Chemistry, or a related discipline.
- 25 years experience in dry-lab drug discovery, computational R&D, or AI/ML-driven biological research,
or postdoctoral research in a relevant computational/biological field.
- Strong knowledge in at least two of the following areas and familiarity with the others:
- Protein engineering (sequence analysis, mutational scanning, stability modeling)
- Structural biology (structure prediction, docking, molecular interactions)
- Multi-omics analytics (RNA-seq, proteomics, scRNA-seq, integrative systems biology)
- Bioinformatics pipelines (annotation, variant analysis, network biology, functional genomics)
- ML-driven molecular/property prediction
- Ability to interpret sequence/structure/omics outputs and contextualize them within drug discoveryworkflows.
- Excellent scientific communication and project coordination abilities.
Job Classification
Industry: Pharmaceutical & Life SciencesFunctional Area / Department: Research & DevelopmentRole Category: Pharmaceutical & BiotechnologyRole: Molecular BiologistEmployement Type: Full timeContact Details:
Company: InnoplexusLocation(s): Pune
Keyskills: Structural Biology Multi-Omics Computational Biology Aiml Drug Discovery Bioinformatics
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