The opportunity

We are seeking an experienced computational biology leader to guide the evaluation and real-world applications of our foundation models. You will bring your expertise in biology and data science to provide crucial scientific direction, ensuring we tackle the most important problems in drug development and translational research. Reporting to the head of Computational Biology, this is a senior individual contributor role within our R&D team that will expand into management as the company grows. You will provide domain expertise to our research team, mentor junior team members, and collaborate closely with our Product and Business Development teams. This role can be based in our Paris office or remote, with expected regular travel to Paris for team meetings.

What you'll be doing

As a Computational Biology Lead, you will:

• Research & Innovation: Identify and develop AI and foundation model approaches to answer key questions in biopharma and translational research. Collaborate with our research team to identify, acquire, or generate new datasets and data modalities to incorporate into our models. Contribute to publications, patents, and case studies showcasing novel applications in pharma R&D.
• Leadership: Represent Bioptimus at conferences, workshops, and client meetings, demonstrating domain expertise and the potential of AI-driven drug development. Mentor junior team members and provide domain expertise to our R&D team.
• Bridge Research & Product: Translate biopharma research questions into actionable machine learning objectives and tasks. Work closely with product, business, and research teams to define feature priorities.
• Stakeholder Engagement: Serve as a trusted scientific partner during external technical discussions. Design proof-of-concept studies, address domain-specific queries, and deliver high-quality presentations that highlight the value of Bioptimus' solutions. Provide ongoing training and support to partners on how to interpret and apply our foundation models in R&D pipelines. Help unlock actionable insights in transcriptomics, proteomics, histology, and beyond.

What you'll bring to the team

The successful candidate will have a ‘team-first’ attitude; be independent, curious, and detail-oriented; thrive in a dynamic, fast-paced environment; and be fun to work with. We value individuals who bring deep domain expertise in pharmaceutical R&D alongside strong hands-on computational skills.

• Educational Background:
  • PhD or equivalent experience in Computational Biology, Bioinformatics, or related field.
• BioPharma R&D Experience:
  • 4+ years professional experience in Biopharma R&D
  • Deep understanding of biopharma R&D use-cases, challenges, tools and processes
  • Ability to break down high-level biopharma use-cases into actionable recommendations for the research & product team (ex: evaluation metrics, data annotations, specific loss function, etc…)
• Computational Biology:
  • Extensive experience working with end-to-end genomics and multi-omics datasets (transcriptomics, single-cell, proteomics, imaging, etc..), from dataset generation & QC, to the analysis and interpretations of results.
  • Demonstrated expertise critically applying machine learning to computational biology, including scientific publications at high-impact journals and/or top conferences in the field.
  • Deep experience in Python/R. Comfortable working in cloud computing environments and with version control systems
• Exceptional Communication Skills:
  • Experience working in cross-functional environments and influencing the decision making of senior/executive stakeholders
  • Capable of engaging both technical and non-technical stakeholders. Adept at crafting compelling presentations and scientific narratives for high-level stakeholders and internal teams.

How to stand out:

• Translational Oncology/Immunology Research: Demonstrated experience leading computational biology efforts in translational research from IND filing to clinical trials.
• Single Cell & Spatial Expertise: Extensive experience in computational biology research, in particular in single cell and spatial domains, applying AI/ML models in translational or clinical research.
• Project Leadership Experience: Demonstrated ability to manage complex projects, and deliver results in a fast-paced environment.
• Internal/External Leadership: A track record of impactful contributions to computational biology, drug discovery & development, or foundation models. Demonstrated success mentoring junior scientists.
• Entrepreneurial Mindset: Experience in a startup or innovative environment, showing adaptability, proactiveness, and eagerness to take on varied responsibilities.
• Stakeholder Management: Proven success in matrixed or consulting activities, shaping product offerings, and ensuring stakeholder satisfaction through ongoing relationship management.

The candidate journey

To be considered, please submit your CV in English. We believe in a transparent and collaborative interview process. Here is what you can expect after submitting your application:

1. Screening: Once you have applied, the hiring team will review your application to determine if your work experience and skills align with the necessary proficiencies of this position.
2. Technical Assessment: Given the technical nature of the role, you will be invited to complete a timed (1.5 hours) technical assessment on a dedicated platform. This stage consists of a short set of R/Python exercises designed to assess your proficiency.
3. Interview Process: Following a successful technical assessment, you will be invited to a series of interviews. The core stages of our process are outlined below. Please note that the order may be adapted and additional conversations may be included to ensure a comprehensive evaluation.

   • Hiring Manager Interview: A call with the Hiring Manager to discuss your background, motivation, and expertise. This will include a deep dive into your technical skills, including your experience with coding and cloud environments.

   • Panel Interview: This stage is a comprehensive technical discussion with the Hiring Manager, Tech Leads, and other members of the team. You will be asked to prepare and deliver a presentation on your past research or a relevant project. The interview may also involve discussing a scientific paper, which will be provided to you in advance. Please note that pre-interview preparation is required for this stage.

   • Final Interview: The last step is a conversation with one of our senior leaders. This is an opportunity to discuss your broader motivations and alignment with the company's vision, and for you to ask any final questions.

4. Offer: Following the completion of the interviews, our hiring team will make a final decision and will be in touch to share the outcome. If the team would like to move forward, we will contact you to discuss the details of our proposed offer. Please note that an offer is contingent upon the successful completion of a reference check.

5. Onboarding: We are happy to have you joining the team. Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you to Bioptimus.

Why this is a unique opportunity

• Shape the future of biology and AI by contributing to groundbreaking work.
• A collaborative and mission-driven work environment.
• Globally competitive salary and equity package.
• Flexible work arrangements, including remote options.
• Opportunities for professional growth and leadership development.