We're Hiring Innovators

We are looking for an R&D Engineer to develop new drug design workflows. This role focuses on prototyping algorithms, testing ideas, and building tools that integrate directly into our platforms.

Scientific background

• Strong understanding of supramolecular chemistry and structural biology.
  

• Solid knowledge of molecular biophysics and biomolecular recognition.
  

• Experience in protein structure modeling and evaluation.

Technical skills

• Strong Python programming skills (functions, classes, data structures) and experience with core analytical Python packages (NumPy, Pandas, etc.)
  

• Familiarity with PyTorch and GPU-based computing.
  

• Experience with Conda environments.
  

• Understanding of ML/DL concepts and model evaluation metrics.
  

• Experience with Linux and GitHub.
  

Soft skills

• Curiosity, initiative, and motivation to engage in research-driven tasks.
  

• Strong communication skills and ability to collaborate effectively.
  

• Consistently reliable in meeting deadlines, attending key meetings, and following through on shared responsibilities.

• Open, honest, and comfortable giving and receiving feedback and iterating based on it.

• Experience with protein structure prediction and/or docking tools (e.g., AlphaFold, HDOCK, HADDOCK).
  

• Familiarity with chemical file formats (PDB, CIF, MOL2, SDF).
  

• Experience working on remote machines and/or cloud platforms (e.g., Google Cloud).
  

• Knowledge of deep learning architectures such as Transformers or GNNs.

We are seeking a strong Software Developer to join our team working on Receptor AI Web, a cutting-edge molecular visualization and drug discovery platform. You will primarily develop and maintain our React/TypeScript frontend, with opportunities to explore 3D visualization, scientific computing, and full-stack architecture as you grow.

• Develop and maintain frontend features using React and TypeScript.

• Work with 3D molecular visualization using NGL library.

• Integrate with RESTful APIs for chemical compound data.

• Optimize performance for large datasets and real-time rendering.

• Debug and refactor existing codebase for better maintainability.

• Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent experience).

• 1+ year of professional software development experience.

• Strong programming skills in JavaScript/TypeScript.

• Solid understanding of React hooks and modern React patterns.

• Experience with state management solutions (Redux preferred).

• Proficiency with version control systems (Git).

• Good problem-solving skills and attention to detail.‍

• Proven ability to contribute effectively both independently and as part of a team.

• 3D Graphics/Visualization - Experience with WebGL, Three.js, or scientific visualization libraries.

• Chemistry/Biology background.

• Data Visualization - Experience with Chart.js, D3.js, or similar libraries.

• Backend knowledge - Familiarity with Python, or API development.

• Familiarity with testing frameworks (Jest, Vitest, React Testing Library).

• Knowledge of responsive design and cross-browser compatibility.

• Understanding of performance optimization techniques.

• Experience with scientific or data-intensive applications.

• Cross-functional exposure (frontend, 3D visualization, scientific computing).

• Professional development opportunities.

• Collaborative and learning-focused environment.

• Self-starter who can take features from concept to production.

• Creative problem-solver who thinks outside the box.

• Interested in the intersection of technology and drug discovery.

• Comfortable learning complex scientific domains.

• Detail-oriented with strong debugging skills.

• Сommunicates technical concepts clearly.

• Open to innovative approaches and unconventional solutions.

We’re looking for a Senior-level computational chemist to join our discovery team and contribute to live hit-to-lead and lead optimization projects. You’ll play a key role in connecting in silico modeling with medicinal chemistry to design better compounds across a wide range of targets. Beyond hands-on modeling, you’ll be expected to take an active role in shaping project strategies, planning modeling efforts, and influencing prioritization decisions based on data.

• Support compound design using molecular modeling tools (e.g., docking, molecular dynamics, FEP, pharmacophore design).

• Interpret SAR data, suggest new analogs, and prioritize compound ideas.
  

• Collaborate with medicinal chemistry teams.
  

• Contribute to planning project workflows and setting modeling priorities.
  

• Drive hypothesis generation and test cycles based on evolving data.
  

• Apply both structure- and ligand-based design strategies.
  

• Contribute to data-driven iteration and project decision-making.

• Ph.D. in Computational Chemistry, Medicinal Chemistry, or a related field with 2–5 years of experience in drug discovery
  – OR –
  Master’s degree with 5+ years of hands-on industry experience in computational drug discovery or related roles
  

• Proven track record of contributing to hit identification, hit-to-lead, or lead optimization programs
  

• Proficiency in molecular modeling platforms
  

• Strong understanding of medicinal chemistry and SAR interpretation
  

• Comfortable working in fast-moving, cross-functional project teams

• Drive real drug discovery with visible impact on pipeline progress
  

• Join a science-first team blending AI and chemistry for next-gen therapeutics
  

• Enjoy flexible working with support for remote collaboration

Is actively contributed to real drug discovery projects and can confidently apply modeling techniques to impact design decisions. Is comfortable balancing scientific depth with practical prioritization and can independently plan and drive modeling strategies within multi-disciplinary projects.

We are looking for a Junior Computational Chemist to join our Drug Discovery team and gain hands-on experience in applying computational methods to modern drug discovery. This role is ideal for recent graduates in chemistry, biochemistry, pharmaceutical sciences, or related fields who are eager to build a career in molecular modeling, cheminformatics, or structure-based drug design. In this role, you will work under the guidance of senior scientists, contribute to live projects, and gain exposure to cutting-edge workflows at the intersection of chemistry, biology, and AI.

• Support hit discovery projects by preparing protein and ligand structures for modeling.

• Run docking workflows and visualize protein–ligand interactions using molecular modeling tools.

• Assist in structure- and ligand-based design tasks across live projects.

• Contribute to the setup and execution of cheminformatics pipelines (e.g., RDKit, Open Babel).

• Document workflows, results, and insights clearly for team discussions.

• Collaborate with interdisciplinary teams and follow technical guidance from senior scientists.

• Explore applications of AI/ML, peptide modeling, and cheminformatics under supervision.

Education & Background

• Final-year student or recent graduate (B.Sc. or M.Sc.) in Chemistry, Biochemistry, Pharmaceutical Sciences, Computational Chemistry, Structural Biology, or related fields.

• Candidates from engineering or physics with exposure to molecular simulations, bioinformatics, or AI in life sciences are encouraged to apply.

Experience & Technical Skills

• Basic understanding of molecular docking principles and exposure to tools such as AutoDock, Glide, or GOLD through coursework, internships, or self-study.

• Basic understanding of core CADD concepts.

• Familiarity with molecular visualization tools (PyMOL, UCSF Chimera, VMD).

• Basic proficiency in Python or another scripting language; experience with Jupyter or Google Colab preferred.

• Coursework, research projects, or self-initiated learning in computational modeling will be considered favorably.

Interpersonal & Organizational Abilities

• Strong scientific curiosity and motivation to learn practical computational skills.

• Good communication skills to discuss findings clearly and work collaboratively in a team environment.

• Openness to feedback and continuous learning in a fast-paced setting

• Experience in academic drug discovery programs, hackathons, or internships at pharma, CROs, or research centers.

• Familiarity with AI/ML frameworks for chemistry (e.g., DeepChem, PyTorch).

• Knowledge of peptide structure or macrocycle modeling principles.

• Mentorship from experts with deep industry experience.
  

• Work on high-impact, real-world drug discovery programs.
  

• Flexible, remote-friendly culture.

• Project Coordination: Support the planning, execution, and monitoring of AI-driven drug discovery projects, ensuring alignment with scientific and strategic goals.

• Timeline & Milestone Tracking: Maintain and update project plans, Gantt charts, and sprint boards using tools such as Jira.

• Cross-functional Communication: Act as a liaison among interdisciplinary teams—biology, chemistry, computational modeling, and AI—facilitating seamless collaboration and effective handoffs.

• Meeting Support: Organize and document internal and external meetings, including drafting agendas, recording decisions, tracking action items, and distributing minutes via Confluence or shared drives.

• Data & Task Integration: Track ongoing tasks, workflows, and iterations; collaborate with scientific leads to update task boards and data registries in Jira or equivalent systems.

• Risk Monitoring: Identify and communicate potential scientific or operational risks to senior management; support proactive issue resolution and contingency planning.

• Documentation & Knowledge Management: Maintain comprehensive and version-controlled project documentation using platforms such as Confluence and Google Drive.

• Compliance & SOP Adherence: Ensure that project documentation and processes comply with internal SOPs and quality standards.‍

• Process Optimization: Participate in retrospectives and continuous improvement initiatives; contribute to the refinement of project management practices and workflows using insights from previous projects.

Education & Background

• Bachelor’s degree in life sciences (Biology, Chemistry, Pharmaceutical Sciences) or a related field; Master’s preferred.

• Basic familiarity with drug‑discovery workflows (medicinal chemistry, in vitro/in vivo assays) and AI‑driven modeling concepts.

Experience & Technical Skills

• 1+ years of experience supporting R&D projects.

• Hands‑on use of project‑management tools (Jira, Confluence, MS Project or equivalent) and proven proficiency maintaining Gantt charts and sprint boards.

• Proven ability to keep timelines, sprint boards, and status reports up to date.

• Strong data‑tracking aptitude: comfortable updating databases/registries and extracting metrics for status reports.

Project Management & Compliance

• Working knowledge of SOPs and quality standards; able to ensure documentation meets regulatory requirements.‍

• Basic skills in assessing risks and escalating issues when needed.

Interpersonal & Organizational Abilities

• Excellent written and verbal communication; adept at coordinating across biology, chemistry, computational modeling, and AI teams.

• Highly organized, detail-oriented, and reliable in following up on actions and commitments.

• Collaborative mindset; comfortable participating in retrospectives and driving continuous‑improvement initiatives.

• English language proficiency at level B2 or higher.

Additional Attributes

• Certification or coursework in project management and/or drug discovery.

• Ability to learn new scientific tools and adapt to evolving workflows on fast‑paced projects.