Principal or Senior Principal Scientist Computational Drug Discovery

Zealand Pharma•Boston, MA

16h•$220,000 - $270,000

About The Position

Zealand Pharma is expanding its global R&D capabilities and establishing new research units in Cambridge, Massachusetts. As part of this growth, Molecular Platform Development is being created to strengthen and advance diverse drug modality capabilities in metabolic disease. In this role as Principal or Senior Principal Scientist – Computational Drug Discovery, the position serves as a senior individual contributor and scientific leader, influencing discovery direction across multiple programs while helping define strategy, culture, and best practices within the new organization. We offer exciting responsibilities: Define and drive computational drug discovery strategy aligned with Zealand Pharma’s metabolic disease portfolio and long-term objectives Co-develop discovery hypotheses and molecular design strategies with experimental colleagues to accelerate iterative design–make–test–analyze learning cycles Lead structure-guided and quantitative modeling approaches from early concept through lead candidate selection Provide structure-guided analysis of target druggability and tractability in order to guide modality suitability assessments Establish and evolve computational discovery capabilities for protein- and peptide-based modalities (including bioconjugates and fusions), integrating physics- and LLM-based methods where they add interpretable value Mentor and support the development of computational scientists and strengthen cross-functional understanding and appropriate use of computational models and analyses Your profile The successful candidate brings strong scientific judgment, a collaborative mindset, and an enterprise perspective, operating as an equal partner to experimental colleagues. The role requires the ability to translate complex quantitative insights into clear, evidence-based recommendations that help teams make high-quality decisions under uncertainty. The position acts with integrity, accountability, and a commitment to rigorous science. Your new team The position sits within Discovery Research: Molecular Platform Development, a new organization being established as part of Zealand Pharma’s Cambridge, MA site. The role reports to the Head of Molecular Platform Development and partners closely with peptide chemistry, protein engineering, biology, translational research, pharmacology, bioanalysis, and CMC colleagues as an embedded member of discovery project teams. Let's bond and be bold We have a unique culture, characterized by excellent teamwork and strong engagement across the organization. And we want you to help us strengthen this culture. Making bonds is at the core of everything we do. From discovering and developing the best new peptide drugs for patients, to engaging with our partners or connecting with each other. We bond through curiosity and playfulness as a team, allowing ourselves to challenge common thinking and drive future innovation. Join us and let's bond and be bold. Interested in bonding with us? Then please apply no later than April 24th, 2026 , or as soon as possible. The applications will be reviewed as they come in. While a cover letter is not required, please include a few sentences in your CV explaining your motivation for applying. We are committed to an inclusive recruitment process and welcome applications from all job applicants. The anticipated base pay range for this position is : $ 220,000 - $ 270,000 About Zealand Pharma A/S Zealand Pharma A/S (Nasdaq: ZEAL) is a biotechnology company focused on advancing medicines for obesity and metabolic health. Combining more than 25 years of peptide R&D expertise with a proprietary data platform that leverages advanced data-driven and AI/ML approaches, Zealand Pharma aims to lead a new era in obesity and metabolic health. To date, more than ten Zealand Pharma-invented drug candidates have entered clinical development, of which two products have reached the market and three candidates are in late-stage development. The Company has collaborations with global pharmaceutical and biotechnology partners for research, development, and commercialization. Founded in 1998, Zealand Pharma is headquartered in Copenhagen, Denmark, with a U.S. presence in Boston, Massachusetts. Learn more at www.zealandpharma.com

Requirements

PhD in Computational Chemistry, Computational Biology, Computational Biochemistry, Structural Biology, Chemical Biology, or a related field (postdoctoral training preferred)
6+ years of relevant post-degree experience (Principal Scientist) or 8+ years (Senior Principal Scientist) in computational drug discovery
Demonstrated track record of computational insights materially influencing programs that have advanced molecules into clinical development
Deep expertise in structure-guided modeling and quantitative/statistical approaches relevant to protein- and peptide-based drug discovery
Proven ability to integrate experimental structural data with quantitative structure–activity reasoning and sequence–structure–function analysis to guide molecular design and prioritization
Strong cross-functional understanding of experimental discovery and early development disciplines (e.g., protein expression, peptide synthesis, formulation/stability, and in vitro/in vivo pharmacology) to support realistic design decisions

Responsibilities

Define and drive computational drug discovery strategy aligned with Zealand Pharma’s metabolic disease portfolio and long-term objectives
Co-develop discovery hypotheses and molecular design strategies with experimental colleagues to accelerate iterative design–make–test–analyze learning cycles
Lead structure-guided and quantitative modeling approaches from early concept through lead candidate selection
Provide structure-guided analysis of target druggability and tractability in order to guide modality suitability assessments
Establish and evolve computational discovery capabilities for protein- and peptide-based modalities (including bioconjugates and fusions), integrating physics- and LLM-based methods where they add interpretable value
Mentor and support the development of computational scientists and strengthen cross-functional understanding and appropriate use of computational models and analyses

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