Requirements
Requires a Bachelor's or Master's degree in architecture, Landscape Architecture, Computational Design, or a related field, with 3-5 years of experience in computational design, architecture, or Landscape Architecture. Must have expertise in automation tools, BIM integration (Revit, Rhino.inside), and strong understanding of architectural principles. Excellent communication and collaboration skills are essential.
Description
Company Overview:Dar, the founding member of the Sidara group, is an international multidisciplinary consulting organization specializing in engineering, architecture, planning, environment, project management, facilities management, and economics. Sidara operates in 60 countries with 20,500 professionals, Dar connects people, places, and communities through innovative solutions to the world's most complex challenges. We deliver projects from inception through completion, embracing challenges to empower communities worldwide. Learn more at www.dar.com.Our Vision and Values:We aspire to be the chosen home of those with a gift for crafting solutions that empower people and an unwavering passion for learning and innovation. Our core values shape our culture and guide our decision-making. We are committed to:ExcellenceResponsibilityEmpowermentConnectivityCourageJob Summary: We are looking for a Computational Designer with a background in Landscape Architecture or Architecture to join our team. This role focuses on leveraging computational design strategies to enhance creativity, efficiency, and performance in Landscape projects. The ideal candidate will have experience working with parametric modelling, automation tools, and performance analysis, ensuring innovative and data-driven design solutions. Responsibilities: • Develop computational design strategies to optimize workflows, automate repetitive tasks, and explore generative design possibilities. • Collaborate with landscape architects, architects, engineers, and other stakeholders to integrate computational methodologies into the design process. • Utilize parametric modelling tools particularly, Rhino and Grasshopper, Programming/Scripting: C#, Python, for developing computational solutions • Conduct performance analysis to assess structural integrity, environmental sustainability, and energy efficiency, ensuring data-driven design decisions. • Provide technical guidance and knowledge to the LS management team as representative of the discipline to ensure the BIM workflow is followed. • Develop and maintain computational workflows and standards within the team, ensuring scalability and efficiency. • Stay informed on emerging technologies in computational design, automation, AI-driven tools, and digital fabrication to enhance design capabilities. Requirements:Education: Bachelor's or master's degree in architecture, Landscape Architecture, Computational Design, or a related field. Experience: 3-5 years of experience in computational design, architecture, or Landscape Architecture Technical Proficiency (required): o Expertise in development of automation tools. BIM integration: Working knowledge of Revit and interoperability between computational tools (Eg. Rhino.inside). Strong understanding of architectural and interior design principles, building systems, materials, and construction techniques. Excellent communication and collaboration skills to work effectively within a multidisciplinary team. Ability to manage multiple projects simultaneously while maintaining high-quality deliverables. A portfolio showcasing computational design projects. Preferred Skills (Bonus): Experience with automation and AI-driven tools for design optimization. Knowledge of site modelling, material research, or computational geometry. Understanding of cloud-based computing or scripting for large-scale data processing for design applications. Understanding of business intelligence and data visualization tools like Power BI * While we carefully review all applications, only candidates meeting the specified requirements will be contacted for further consideration. We appreciate your understanding and thank all applicants for their interest.