6 Simulation Models Jobs

As an EDA Engineer, you will be responsible for developing, maintaining, and optimizing analog/mixed-signal IC design flows in Cadence Virtuoso and related EDA tools. Your role will involve creating, modifying, and optimizing SKILL scripts for automation of layout, schematic, verification, and design environment tasks. You will manage Component Description Format (CDF) parameters and configurations for foundry PDK and CDK components/libraries. Working extensively with the OpenAccess (OA) database API, using C++, Python, and Tcl, will be a key aspect of your responsibilities. You will be involved in reading, writing, and manipulating design data, including schematic, layout, connectivity, and library information. Developing automation tools and workflows leveraging OpenAccess to integrate schematic and layout views, support PDK/CDK validation, and assist in design data migration or QA will also be part of your tasks. Troubleshooting issues related to PDK integration, OA database consistency, schematic-layout synchronization, and environment setups will be within your scope. Additionally, you will document technical processes, create reusable automation scripts, and contribute to team best practices. Collaboration with AI and software teams to integrate EDA tools into the AI co-pilot platform and support continuous improvement of design automation is essential. To succeed in this role, you should possess 3-8 years of hands-on experience working with Cadence Virtuoso analog/mixed-signal design flows. Strong proficiency in SKILL scripting for automation within Cadence layout and schematic environments is required. Proven experience managing and customizing CDF files for parametric device libraries in Cadence is also important. Hands-on experience with the OpenAccess (OA) database API, familiarity with OA schema, and the ability to program in C++, Python, or Tcl for developing tools/scripts are necessary skills. A deep understanding of foundry PDK/CDK structures, experience automating schematic and library processes using scripting languages, solid knowledge of schematic editors/viewers, and maintaining schematic-layout synchronization are also vital for this role. Moreover, you should have strong UNIX/Linux command-line skills, experience with version control systems/tools used in EDA environments, excellent communication skills, and the ability to operate effectively in a startup team environment. Preferred qualifications include previous work experience at Cadence or semiconductor companies specializing in Virtuoso toolchains, experience with Spectre, ADE simulation, analog verification flows, understanding of semiconductor process technology, and familiarity with AI/ML integration in design tools. For further information or to express interest in this position, please contact rekha.cxc@careerxperts.com.,

You will be responsible for ensuring the completion of experiments and generating accurate and reproducible data. This will involve developing relevant models, validating them, and supervising laboratory/pilot plant experiments within the research area. Your duties will include sample preparation, characterization, and evaluation, as well as organizing facilities and resources for experiments. Additionally, you will participate in pilot plant operations/studies and use the results as boundary conditions for model development. Supporting plant operations, collecting data, conducting analysis, uploading reports, and preparing Internal Technical Reports are also part of your responsibilities. To qualify for this role, you must have a PhD in Biology/Chemistry/Chemical Engineering with specialization in the relevant research area. A minimum of 2-3 years of research experience is required. Your skills and competencies should include conducting literature surveys, compiling information for analysis, developing work methods, and preparing SOPs for experiments. You should be able to design and plan experiments, use simulation models, study technology offers, and process engineering documents. Familiarity with process engineering design activities, relevant tools, and applicable guidelines, codes, standards, and legislations in the field of research is essential.,

Join our dynamic Workforce Planning (WFP) team within Consumer and Community (CCB) Operations division and be part of a forward-thinking organization that leverages data science to optimize workforce efficiency. Contribute to innovative projects that drive impactful solutions for Chase's operations. As an Operations Research Analyst within the WFP Data Science team, you will tackle complex and high-impact projects. Your responsibilities will include designing and developing optimization models and simulation models, supporting OR projects either individually or as part of a team, and collaborating with stakeholders to understand business requirements and define solution objectives clearly. It is crucial to identify and select the correct method to solve problems while staying up to date on the latest OR methodologies and ensuring the robustness of any mathematical solution. Additionally, you will be expected to develop and communicate recommendations and OR solutions in an easy-to-understand manner, leveraging data to tell a story. Your role will involve leading and persuading others positively to influence team efforts and help frame business problems into technical problems with feasible solutions. The ideal candidate should possess a Master's Degree with 4+ years or a Doctorate (PhD) with 2+ years of experience in Operations Research, Industrial Engineering, Systems Engineering, Financial Engineering, Management Science, or related disciplines. You should have experience supporting OR projects with multiple team members, hands-on experience developing simulation models, optimization models, and/or heuristics, a deep understanding of the mathematics and theory behind Operations Research techniques, and proficiency in Open Source Software (OSS) programming languages like Python, R, or Scala. Experience with commercial solvers like GUROBI, CPLEX, XPRESS, or MOSEK, as well as familiarity with basic data table operations (SQL, Hive, etc.), is required. Demonstrated relationship-building skills and the ability to make things happen through positive influence are essential. Preferred qualifications include advanced expertise with Operations Research techniques, prior experience building Reinforcement Learning Models, extensive knowledge of Stochastic Modelling, and previous experience leading highly complex cross-functional technical projects with multiple stakeholders.,

Join our dynamic Workforce Planning (WFP) team within Consumer and Community (CCB) Operations division and be part of a forward-thinking organization that leverages data science to optimize workforce efficiency. Contribute to innovative projects that drive impactful solutions for Chase's operations. As an Operations Research Analyst within the WFP Data Science team, you will tackle complex and high-impact projects. You will assess unstructured problems, develop practical strategies, and propose solutions to enhance decision-making processes. Collaborate with management to prioritize, time, and deliver next-gen operations research solutions. Your responsibilities will include designing and developing optimization models and simulation models, supporting OR projects either individually or as part of a project team, collaborating with stakeholders to understand business requirements and define solution objectives clearly, selecting appropriate methods to solve problems while staying updated on the latest OR methodologies, ensuring the robustness of mathematical solutions, developing and communicating recommendations and OR solutions in an easy-to-understand manner using data to tell a story, leading and persuading others to positively influence team efforts, and helping frame a business problem into a technical problem to achieve feasible solutions. To be considered for this role, you should possess a Master's Degree with 4+ years or a Doctorate (PhD) with 2+ years of experience in Operations Research, Industrial Engineering, Systems Engineering, Financial Engineering, Management Science, or related disciplines. You should have experience supporting OR projects with multiple team members, hands-on experience in developing simulation models, optimization models, and/or heuristics, a deep understanding of the math and theory behind Operations Research techniques, proficiency in Open Source Software (OSS) programming languages like Python, R, or Scala, experience with commercial solvers like GUROBI, CPLEX, XPRESS, or MOSEK, and familiarity with basic data table operations (SQL, Hive, etc.). Additionally, you should have demonstrated relationship building skills and a superior ability to make things happen through positive influence. Preferred qualifications include advanced expertise with Operations Research techniques, prior experience in building Reinforcement Learning Models, extensive knowledge of Stochastic Modelling, and previous experience in leading highly complex cross-functional technical projects with multiple stakeholders.,

House of Shipping is seeking a high-caliber Data Science Lead to join their team in Hyderabad. With a background of 15-18 years in data science, including at least 5 years in leadership roles, the ideal candidate will have a proven track record in building and scaling data science teams in logistics, e-commerce, or manufacturing. Strong expertise in statistical learning, ML architecture, productionizing models, and impact tracking is essential for this role. As the Data Science Lead, you will be responsible for leading enterprise-scale data science initiatives in supply chain optimization, forecasting, network analytics, and predictive maintenance. This position requires a blend of technical leadership and strategic alignment with various business units to deliver measurable business impact. Key responsibilities include defining and driving the data science roadmap across forecasting, route optimization, warehouse simulation, inventory management, and fraud detection. You will work closely with engineering teams to architect end-to-end pipelines, from data ingestion to API deployment. Proficiency in Python and MLOps tools like Scikit-Learn, XGBoost, PyTorch, MLflow, Vertex AI, or AWS SageMaker is crucial for success in this role. Collaboration with operations, product, and technology teams to prioritize AI use cases and define business metrics will be a key aspect of the job. Additionally, you will be responsible for managing experimentation frameworks, mentoring team members, ensuring model validation, and contributing to organizational data maturity. The ideal candidate will possess a Bachelor's, Master's, or Ph.D. degree in Computer Science, Mathematics, Statistics, or Operations Research. Certifications in Cloud ML stacks, MLOps, or Applied AI are preferred. To excel in this role, you should have a strategic vision in AI applications across the supply chain, strong team mentorship skills, expertise in statistical and ML frameworks, and experience in MLOps pipeline management. Excellent business alignment and executive communication skills are also essential for this position. If you are a data science leader looking to make a significant impact in the logistics industry, we encourage you to apply for this exciting opportunity with House of Shipping.,

Mechanical Engineering / Industrial Engineering/ Production & Manufacturing Engineering, excellent academic record required Minimum 3-5 Yrs. of Manufacturing Experience. Skills: Experience with Simulation Software Anylogic or Siemens Tecnomatix Plant simulation Minimum 2+ years of direct modelling experience. Excel, PowerPoint a must. Technical Background: Direct experience working on building, analyzing DES Model using Tecnomatix / Anylogic Value stream analysis, facilities layout production system design, manufacturing process design and systems design thinking. Should be comfortable building models and writing scripts to run special logic using both softwares. Able to understand process logic and translate them into simulation models. Showcase analytical skills to evaluate data output from Simulation models and drive those towards recommendation for the client. Apply mathematical operations to theoretical and practical manufacturing and industrial situations. Good verbal and written communication skills. Able to communicate well with client team members. In understanding the requirements for the modelling and conveying recommendation and results based on the problem statement. Knowledge of Layout Analysis - Plant Simulation & Factory Flow analysis, Operations research, Plant optimization, Discrete Event simulation, & Methods Engineering. Experience with Monte Carlo analysis and other parametric experiments to evaluate the impact of changes in systems. Strong analytical skills and the ability to translate findings and recommendations into impactful presentations for various stakeholders.