Senior Data Scientist, Computational Chemistry

<p><strong>Why Join Us?</strong></p> <p>As a member of the Parabilis Medicines team, you will be a part of an organization dedicated to creating extraordinary medicines for diseases with urgent unmet needs, harnessing our proprietary peptide platform to transform treatment possibilities for patients. Parabilis is a clinical-stage biopharmaceutical company dedicated to unlocking high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. </p> <p>Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and AR<sup>ON</sup> into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.</p> <p><strong>What’s the opportunity?</strong></p> <p>We are seeking a highly talented and self-motivated person to contribute to the development of the Computational Drug Discovery group, a strategic function in Data Science that is part of Parabilis’s platform discovery engine for HeliconTM stapled-peptide drugs.  The skill sets of the group includes state-of-the-art machine learning/generative AI, molecular modeling, cheminformatics and data science towards the discovery and development of HeliconTM stapled-peptide drugs.</p> <p> </p> <p>You’ll be part of a data science team that is a central pillar of Parabilis’s innovative discovery platform and pipelines targeting “undruggable” genes of major therapeutic interest to patients. Our data science team is an integrated team, ranging from computational biology, bioinformatics, computational drug discovery, research informatics and engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science, from building the discovery pipeline to supporting and developing our discovery .</p> <p> </p> <p>Responsibilities</p> <p> </p> <ul> <li>Provide computational expertise towards, but not limited to, ternary complex designs for degraders and other proximity-based modalities, hit-to-lead progression using multi-objective optimization, initiating new projects, new drug-target assessments and advancing drug-pipeline projects towards the clinic.</li> </ul> <p> </p> <ul> <li>Identify, implement, and apply 3D modeling techniques for sampling HeliconTM peptide conformations in presence of a target, in ternary complex, and in different physiological environments.</li> <li>Analyze and derive 3D peptide-structure relationships.</li> <li>Exemplify scientific leadership by partnering across functions and working within a team of talented and passionate scientists to discover drugs.</li> <li>Interface with internal and external partners.</li> </ul> <p> </p> <p><strong>What you’ll need to be successful:</strong></p> <p><strong> </strong></p> <ul> <li>PhD in Computational Chemistry, Protein Engineering, Chemistry, Physics, Macromolecular sciences or close-related field</li> <li>5+ years of pharma/biotech industry experience in computational rational drug .</li> <li>Demonstrated experience with ternary complex design and understanding, peptide design or protein engineering and a good understanding of peptide structure-property relationships (e.g. helicity and amphiphilicity metrics, cell penetration).</li> <li>Demonstrated mastery of modern computational chemistry including, but not limited to, peptide folding and docking, use of co-folding foundation models, such as Boltz, structure-based design (receptor and ligand-based), scaffold hopping, docking and conformational analysis.</li> <li>An understanding of modern drug discovery including, but not limited to, medicinal chemistry, multi-parametric optimization, molecular recognition principles, and the ability to adapt and translate these principles to stapled peptides.</li> <li>Excellent communication and collaboration skills, with the ability to work well in a multidisciplinary environment</li> <li>Excellent organizational skills and attention to detail, with a strong passion for learning new concepts and technologies</li> <li>Expertise in one or more peptide modeling environments (e.g. ICM, Rosetta, Amber, GROMACS) and methods (enhanced sampling MD, Monte Carlo, MSM).</li> <li>Demonstrated understanding of critical assessment of molecule-property data and predictive model quality.</li> <li>Demonstrated understanding of experiments behind the data that can be translated to computational analysis.</li> <li>Experience with command line modeling applications.</li> <li>Familiarity with cloud computing environments.</li> <li>Strong scientific programming skills (Python) in a Linux environment.</li> <li>Experience with enterprise research informatics systems such as Dotmatics and chemical and biological data warehouses is a plus.</li> <li>Familiarity with concepts in machine learning.</li> <li>Familiarity with cheminformatics techniques is a plus.</li> <li>Familiarity with use of LLMs and IDEs, such as Cursor, to enhance workflows, productivity and innovation is a plus.</li> <li>Demonstrated use of AI tools in your current role and responsibilities is required. Advanced or innovated use of AI is a strong plus.</li> </ul> <p> </p> <p><strong>Core Values</strong></p> <p><strong> </strong></p> <p>Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.</p> <ul> <li><strong>Growth-Minded.</strong> We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.</li> <li><strong>In(ter)dependent.</strong>We are fiercely <em>independent</em> as a leader in defying the limitations of current therapeutic modalities, and <em>interdependent</em> as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.</li> <li><strong>Patient-focused.</strong>We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.</li> <li><strong>All-In.</strong>We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.</li> </ul> <p>The base salary range for this position is $145,000 - $175,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.</p> <p>As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.</p> <p><strong> </strong></p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>