Senior Scientist Computational Chemistry at argenx

Ghent, Flanders, Belgium -

Full Time

Start Date

Immediate

Expiry Date

08 Mar, 26

Salary

0.0

Posted On

08 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Computational Chemistry, Cheminformatics, Structural Biology, Structure-Based Drug Design, Virtual Screening, Molecular Modeling, AlphaFold, AI/ML Applications, Medicinal Chemistry, Drug-Likeness, CRO Management, Data Integration, Predictive Modeling, Collaboration, Communication, Problem-Solving

Industry

Biotechnology Research

Description

Join us as we transform immunology and deliver medicines that help autoimmune patients get their lives back. argenx is preparing for multi-dimensional expansion to reach more patients through a rich pipeline of differentiated assets, led by VYVGART, our first-in-class neonatal Fc receptor blocker approved for the treatment of gMG, and with the potential to treat patients across dozens of severe autoimmune diseases. We are building a new kind of biotech company, one that maintains its roots as a science-based start-up and pushes our commitment to innovate across all corners of our business. We strive to inspire and grow our company, our partnerships, our science, and our people, because when we do, we deliver more for patients. About the role Argenx is establishing a new department dedicated to small molecule and peptide drug discovery. We are seeking an experienced Computational Chemist (8+ years in biopharma) to lead computational approaches for small molecule drug discovery. This role combines structure-based drug design (SBDD) expertise with strategic vision for leveraging AI-driven models and external partnerships. You will set up the in silico design ecosystem (software implementation, selection of CRO’s or expert consultants) in order to enable data-driven optimization of drug candidates. This position is based at our facility in Zwijnaarde (Ghent), and expects on-site presence. Key Responsibilities Structure-Based Drug Design (SBDD) Shorten DMTA cycles by in silico filtering of new design ideas. Collaborate with medicinal chemists to optimize potency and selectivity. Set up a software ecosystem (in house or through collaboration) that enables you of interpreting structural biology data and allowing to dock and rank new molecules. Stay abreast of cutting edge technologies like AlphaFold, OpenFold, Boltz or any emerging convolutional models for protein-ligand interaction insights. Collaborate with structural biology group in Argenx to obtain an in silico design ecosystem fully integrated with ongoing efforts. AI-Driven Predictive Modeling Shorten DMTA cycles by implementing models (through collaboration, CRO, expert consultants) that aid obtaining a drug like molecule. Collaborate with both medicinal chemists and ADMEt/DMPK expert. Identify and manage partnerships with leading AI/ML platform providers. Leverage state-of-the-art models for potency, ADME/Tox prediction, and generative design. Provide strategic input on realistic applications of AI in drug discovery. Data Integration & Visualization Aid in the aggregation and harmonization data from CROs and internal sources. Leverage different data streams to obtain better predictive models. Profile PhD or equivalent in Computational Chemistry, Cheminformatics, Structural Biology, or related field. 8+ years of experience in computational chemistry within biopharma or biotech. Proven expertise in SBDD, virtual screening, and molecular modeling. Hands-on experience with AlphaFold or similar protein prediction tools. Familiarity with AI/ML applications in drug discovery and ability to evaluate external platforms. Strong understanding of medicinal chemistry principles and drug-likeness. Experience managing CROs and external technology partnerships. Ability to work independently and collaboratively within a team. Excellent communication and interpersonal skills for effective collaboration. Fluent in written and spoken English to ensure clear and effective information exchange. Demonstrated ability to take initiative and address challenges proactively. Dynamic and practical problem-solving approach with a focus on delivering tangible results. Offer The opportunity to establish a new role within the organization, contributing to shaping its future direction. A competitive salary package accompanied by comprehensive benefits. Working in a human-sized, dynamic, rapidly growing biotech company, providing an engaging work environment. #LI-onsite At argenx, all applicants are welcomed in an inclusive environment. They will receive equal 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 applicable legally protected characteristics. argenx is proud to be an equal opportunity employer. Before you submit your application, CV or any other personal details to us, please review our argenx Privacy Notice for Job Applicants to learn more about how argenx B.V. and its affiliates (“argenx”) will handle and protect your personal data. If you have any questions or you wish to exercise your privacy rights, please contact our Global Privacy Office by email at privacy@argenx.com. argenx is a global immunology company dedicated to improving the lives of people suffering from severe autoimmune diseases. Through our rich pipeline of first-in-class therapies, led by VYVGART®, we are accelerating progress toward our bold 2030 vision: to reach 50,000 patients and transform the landscape of autoimmune treatment. Our innovation mission combines with meaningful work and endless opportunities for growth to create once-in-a-career experiences. argonauts work in locations around the globe including Belgium, Boston, Japan and Amsterdam. There's more to discover at argenx, where our passion inspires bold possibility. argenx honors the terms of our written agreements with the recruiting and staffing agencies that we retain and contract with to assist us with talent searches and other recruiting needs. Accordingly, all resumes and referrals that recruiting and staffing agencies proactively share with argenx that (i) were not solicited or requested by argenx’s internal Talent Acquisition team and (ii) were sent in the absence of a valid, written agreement between argenx and the firm, recruiter, or agency, may be pursued by argenx and are ineligible for payment of referral or other fees. We encourage you to be cautious of recruiting scams and fictious communications that pretend to be from argenx employees. These scams are designed by fraudsters to get personal information (e.g., social security numbers, bank account information, dates of birth), money or payments from job seekers as part of a “recruiting” process. argenx does not request financial information or money from job seekers. Legitimate emails from argenx employees end in “@argenx.com.” Fraudsters disguise themselves by using similar email addresses (e.g., @argenxhr.com, @argenxcareer.com, etc.) or public domains (@gmail.com, @yahoo.com, etc.). They may use photographs and names of real argenx employees for their fake interviews. argenx does not recruit or post positions on RingCentral, Facebook, or Craig’s List. Our formal recruitment process includes interviews with members of argenx’s talent acquisition team and other interviewers that occur in person at our offices, or via Zoom or Teams video calls. Interview processes that involve a formal offer from argenx will include written employment documentation on official argenx letterhead. argenx takes prompt appropriate and responsive action to fraudulent recruiting efforts when we become aware of them. If you believe you have been victimized by an employment application or a fraudulent recruiting scam, you can contact your local law enforcement authority for guidance or the FBI’s Internet Crimes Complaint Center at www.IC3.gov to file a complaint.

Responsibilities

The role involves leading computational approaches for small molecule drug discovery, focusing on structure-based drug design and AI-driven predictive modeling. The candidate will collaborate with medicinal chemists and structural biology groups to optimize drug candidates and set up an in silico design ecosystem.