61 Jmp Jobs - Page 3

Plan and execute advanced microbiological research to develop new products and optimize existing processes. Conduct microbial culturing, isolation, identification, and characterization using classical and molecular biology techniques.

locationsIndia, Bangalore time typeFull time posted onPosted 12 Days Ago job requisition idJR0273871 Job Details: About The Role : About the Role: Join our innovative and inclusive Logic Technology Development team as a TD AI and Analytics Engineer, where diverse talents come together to push the boundaries of semiconductor technology. You will have the opportunity to work in one of the world's most advanced cleanroom facilities, designing, executing, and analyzing experiments to meet engineering specifications for our cutting-edge processes. This role offers a unique chance to learn and operate a manufacturing line, integrating the many individual steps necessary for the production of complex microprocessors. What We Offer: We are dedicated to creating a collaborative, supportive, and exciting environment where diverse perspectives drive exceptional results. At Intel, you will have the opportunity to transform technology and contribute to a better future by delivering innovative products. Learn more about Intel Corporation's Core Values here. Benefits: We offer a comprehensive benefits package designed to support a healthy and fulfilling life. This includes excellent medical plans, wellness programs, recreational activities, generous time off, discounts on various products and services, and many more creative rewards that make Intel a great place to work. Discover more about our amazing benefits here. About the Logic Technology Development (LTD) TD Intel Foundry AI and Analytics Innovation Organization: Intel Foundry TD's AI and Analytics Innovation office is committed to providing a competitive advantage through End-to-End AI and Analytics Solutions, driving Intel's ambitious IDM2.0 goals. Our team is seeking an engineer with a background in Data Engineering, Software Engineering, or Data Science to support and develop modern AI/ML solutions. Explore what life is like inside Intel here. Key Responsibilities: As an Engineer in the TD AI office, you will collaborate with Intel's factory automation organization and Foundry TD's functional areas to support and develop modern AI/ML solutions. Your primary responsibilities will include. Developing software and data engineering solutions for in-house AI/ML products. Enhancing existing ML platforms and devising MLOps capabilities. Understanding existing data structures in factory automation systems and building data pipelines connecting different systems. Testing and supporting full-stack big data engineering systems. Developing data ingestion pipelines, data access APIs, and services, monitoring and maintaining deployment environments and platforms, creating technical documentation, and collaborating with peers/engineering teams to streamline solution development, validation, and deployment. Managing factory big data interaction with cloud environments, ORACLE, SQL, Python, Software architecture, and MLOps. Interfacing with process and integration functional area analytics teams and customers using advanced automated process control systems. Qualifications: Minimum Qualifications: Master's or PhD degree in Computer Science, Computer Engineering, or a related Science/Engineering discipline. 3+ years of experience in data engineering/software development and knowledge in Spark, NiFi, Hadoop, HBase, S3 object storage, Kubernetes, REST APIs, and services. Intermediate to advanced English proficiency (both verbal and written). Preferred Qualifications: 2+ years in data analytics and machine learning (Python, R, JMP, etc.) and relational databases (SQL). 2+ years in a technical leadership role. 3+ months of working knowledge with CI/CD (Continuous Integration/Continuous Deployment) and proficiency with GitHub and GitHub Actions. Prior interaction with factory automation systems. Application Process :By applying to this posting, your resume and profile will become visible to Intel recruiters, allowing them to consider you for current and future job openings aligned with the skills and positions mentioned above. We are constantly working towards a more connected and intelligent future, and we need your help. Change tomorrow. Start today. Job Type: Experienced Hire Shift: Shift 1 (India) Primary Location: India, Bangalore Additional Locations: Business group: As the world's largest chip manufacturer, Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in theTechnology Development and Manufacturing Groupare part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moores Law to bring smart, connected devices to every person on Earth. Posting Statement: All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance. Position of Trust N/A Work Model for this Role This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. *

Job Title: Principal Bio-Statistician-Non clinical statistic Location: Hyderabad About The Job As part of the development of Sanofis pharmaceutical products, the R&D Data Sciences department and more specifically the Statistics department for the Chemical Manufacturing Control (CMC) (CMC Statistics), is responsible for contributing to statistical support, modeling, digitalization, decision-making and filing of new product registration files, Our Hubs are a crucial part of how we innovate, improving performance across every Sanofi department and providing a springboard for the amazing work we do Build a career and you can be part of transforming our business while helping to change millions of lives ReadyAs CMC statistician within our Data Sciences/ CMC Statistics youll be supporting the CMC activities for process, analytical methods and formulation development, for several CMC sites in the world, We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve peoples lives Were also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible Ready to get started Major Responsibilities Under supervision of Statistical Project Leader and/or Group Head, contribute to the reliability, scientific quality and optimization of project support from target identification to process development, by providing appropriate Non-Clinical statistical support: Accountable for all assigned statistical deliverables related to one study or activities in the Non-Clinical development area: Perform statistical analyses of data from the laboratories using R and possibly other languages (SAS, ?) or standard statistical software used in Sanofi (JMP, SIMCA, internal tools), to deliver statistical reports/memo Contribute to the development and support of statistical end-user tools (mainly RShiny) Participate to internal working groups and contribute to develop state-of-the art methodologies and statistical approaches Respect Policies, Standards, external guidelines and processes Presentation of statistical work package results to project team members and stakeholders About You Experience: Strong expertise in the field of non-clinical statistics applied to biopharmaceutical development Basic knowledge of pharmaceutical research and development process Scientific rigor and demonstrated level of independence to run statistical work packages For positions supporting Process Development/CMC consider the following: Proven expertise of industrial statistics (descriptive & inferential statistics, statistical process control), design of experiments, multivariate data analysis (PCA, PLS and related methods), statistical modelling and simulation Knowledge of CMC regulatory guidelines (EMA, FDA, ICH Quality, Pharmacopeias), QbD principles and ability to prepare statistical analysis for regulatory dossiers, Use of standard commercial software e-g JMP, SIMCA, MODDE Able to work in departmental computing environment, do advanced statistical analyses using R and possibly other languages (SAS, ?) Soft and technical skills: Excellent interpersonal and communication skills Education: Master in statistics or related discipline Languages: Fluent in English Why choose us Bring the miracles of science to life alongside a supportive, future-focused team, Discover endless opportunities to grow your talent and drive your career, whether its through a promotion or lateral move, at home or internationally, Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact, Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeksgender-neutral parental leave, Be part of a collaborative team Work for several sites internationally Be involved in crucial statistical activities for the company like in the regulatory dossiers null

Degree in EE/ME/Materials/Physical Sciences. Experience with drop/shock/vibration testing. Skilled in failure analysis (SEM, CT, FTIR, MS). Knowledge of DOE, FMEA. Proficient in JMP, Weibull++ for data analysis. Minimum 3 to 12 yrs IT experience.

Your role The candidate should experience in managing Quality / Process Excellence initiative for large engagement. Must have led/driven Six Sigma and Lean projects. She/he need to have the leadership ability to implement the Six Sigma project directed by Master Black Belts (MBB). She/he should be comfortable with managing and driving complex process changes. Must have worked in cross functional teams and demonstrated ability to drive change in the process. Communicate regularly to report to both LSS and other improvement at Project / Engagement level for better engagement. Your profile She/he should have a valid LSS GB (Lean Six Sigma Green Belt) and LSS BB both (Lean Six Sigma Black Belt) certificates Good exposure in LSS DMAIC Project implementation. Good business insight well versed with all key IT business requirement. She/he should have a clear and effective communication skill to succeed in their roles as Six Sigma leaders, mentors, coaches and trainers. Must be able to speak the language of the C-suite and the project floor equally well. Good problem solving and presentation skills. Knowledge of advanced statistical tools like Minitab tool, JMP etc (for doing DOE, AVOVA, simulation etc) Understanding of basic and advanced statistical techniques (in Minitab tools) LSS Trainer (@YB, GB level) What you'll love about working here Were committed to ensure that people of all backgrounds feel encouraged and have a sense of belonging at Capgemini. You are valued for who you are, and you canbring your original self to work. Every Monday, kick off the week with a musical performance by our in-house band - The Rubber Band. Also get to participate in internalsports events, yoga challenges, or marathons. At Capgemini, you can work oncutting-edge projectsin tech and engineering with industry leaders or createsolutionsto overcome societal and environmental challenges.

About the Team: Join a world-class product development organization at IBM, driving innovation across IBM Z and POWER System servers, Storage and Quantum. The Thermal and Mechanical Design team is seeking a skilled professional in thermal modeling with hands-on experience in building, testing, and validating thermal solutions. You’ll be part of a multidisciplinary team developing high-performance, high-reliability server hardware. Role Overview: As a Thermal Modeler, you will design and optimize IBM module and server hardware systems to meet thermal and mechanical requirements. You’ll collaborate with cross-functional teams to ensure designs meet performance, safety, and manufacturability standards. Your work will involve simulation, validation, and providing actionable insights to guide engineering decisions. Key Responsibilities: Develop steady-state and transient CFD-based thermal models using CAD and FVM tools. Acquire and analyze material properties to enhance model accuracy. Validate simulation predictions through lab testing and data analysis. Prepare detailed reports and presentations for stakeholders. Provide design guidelines for thermal hardware components including laminates, TIMs, cold plates, chips, GPUs, HBMs, and actuation hardware. Influence design decisions to ensure robust thermal solutions for IBM server systems. Required education Master's Degree Preferred education Doctorate Degree Required technical and professional expertise Master’s or PhD in Mechanical Engineering with a focus on Thermal or Structural Mechanics. 3+ years of experience in FEM and/or CFD. Proficiency in CAD tools (SolidWorks preferred) and simulation tools like Ansys. Experience with lab tools and design for manufacturability. Strong communication, problem-solving, and time management skills. Ability to work independently and in cross-functional teams. Preferred technical and professional experience 5+ years of experience in thermal modeling and FEA/FVM using tools like FloTherm, SixSigmaET (Celsius), Ansys IcePak, or Fluent. Experience in structural FEA for stress, strain, and warpage prediction. Knowledge of moisture diffusion and swelling simulations. Familiarity with server and computer architecture. Expertise in thermal management of microelectronic packages. Hands-on experience with lab tools such as laser flash conductivity and DSC. Proficiency in applied statistics and DOE using tools like Minitab or JMP. Programming experience in MATLAB, Python, LabVIEW, or C++.

Overview: Join IBM’s elite product development team driving innovation across IBM Z, POWER Systems, Storage and Quantum. We are seeking a skilled mechanical modeler with a strong background in simulation, design, and hardware validation to support high-performance and high-reliability server solutions. Role Summary: As a Mechanical Modeler, you will design and optimize module and server hardware systems to meet stringent thermal and mechanical requirements. You’ll collaborate across disciplines to ensure designs meet performance, reliability, safety, and manufacturability standards. This role involves simulation, lab testing, and providing actionable insights to guide engineering decisions. Key Responsibilities: Develop and simulate system-level hardware models using CAD and FEA tools. Acquire or collaborate to obtain accurate material properties for modeling. Analyze qualification test data and validate against simulation results. Prepare detailed technical reports and presentations for stakeholders. Provide design guidelines for components such as laminates, TIMs, coolers, chips, GPUs, HBMs, and load actuation hardware. Influence design decisions to ensure robust packaging and system integration. First-level packaging (chip, laminate, module) and module-to-socket integration. Required education Master's Degree Preferred education Doctorate Degree Required technical and professional expertise Master’s/PhD in Mechanical Engineering. 3+ years of experience in Finite-Element Modeling (FEM). Proficiency in CAD (SolidWorks preferred) and FEM tools (ANSYS or Abaqus). Ability to create scripts (APDL, Python) beyond GUI modifications. Experience in design for manufacturability (DFM). Hands-on lab experience. Strong communication, problem-solving, and time management skills. Ability to work independently and in cross-functional teams. Familiarity with electronic packaging and heterogeneous integration. Preferred technical and professional experience 5+ years in mechanical modeling. Experience in static structural FEA (stress, strain, warpage prediction). Moisture diffusion and swelling simulation expertise. Knowledge of server/computer architecture. Experience with lab toolstensile testers (Instron/MTS), DMA, TMA, TGA. Applied statistics and DOE knowledge (Minitab, JMP). Programming experience in Matlab, Python, LabView, or C++.

Tesla's Electronics Supplier Industrialization Engineering team plays a crucial role in developing and qualifying critical component and electronic part top-level assembly processes with our suppliers. We provide regional support for New Product Introduction (NPI) and legacy product management within the supply chain. This encompasses everything from early supplier sourcing assessments (in collaboration with the Tesla sourcing and design teams) and make-sourcing decisions, to industrialization and quality control activities. This position demands excellent communication skills, strong supplier management expertise, a willingness to travel domestically and internationally, and the ability to make critical decisions in time-sensitive situations. The role supports a diverse product portfolio, including low/high voltage products, controllers, audio and sensing projects, and optical lens and camera projects. Responsibilities Support Design for Manufacturing (DFM) principles during early product development, providing valuable feedback to NPI SIE (Supplier Industrialization engineer) and design teams. Conduct onsite supplier audit and provide assessment for sourcing decision, develop new suppliers to meet Tesla sourcing requirements. Drive continuous improvement in supplier scalability, cost, and quality performance. Manage and optimize supplier On-Time Delivery (OTD) performance. Oversee supplier production capacity and operations management. Facilitate clear communication of technical requirements between suppliers and Tesla's GSM, SIE, and Design teams. Conduct supplier audits to ensure compliance with part performance, delivery, and reliability expectations. Collaborate with Tesla supply chain teams to establish optimal performance specifications and supplier metrics. Lead, track, and improve supplier manufacturing process development and launch readiness for new products and design changes. Manage and enhance production and product quality. Guide suppliers in developing robust processes and procedures for efficient, high-quality product manufacturing. Follow up and drive SCAR (supplier corrective actions review) with supplier. Validate supplier corrective actions for design and/or process changes, ensuring they are sustainable and implemented across manufacturing lines and suppliers to prevent recurrence. Contribute to the evaluation of new or alternative materials for improved design, manufacturability, or cost reduction. Requirements Minimum 5 years of experience in supply chain or mechanical engineering; experience with Printed Circuit Board Assemblies (PCBAs), Printed Circuit Boards (PCBs) and PCBA top-level assemblies (TLAs) is highly preferred. BS degree in Electrical, Mechanical, Industrial, or Manufacturing Engineering, or demonstrable equivalent experience and exceptional ability. Proven experience with Design for Manufacturing (DFM) and Design for Assembly (DFA). Practical experience with Six Sigma methodologies; DAMIC experience is a plus. Solid hands-on experience of quality statistical analysis tools and applications (e.g., JMP, Minitab). Strong mechanical background, including statistical tolerance analysis, design quality assessment, and improvement techniques. Proficiency in GD&T and 3D CAD software. Demonstrated supplier development and management skills. Self-motivated and capable of working independently. Hands-on and adaptable to a fast-paced environment. Willingness to travel domestically and internationally up to 50% of the time, often with short notice, to engage with Contract Manufacturers (CMs).

The Position The Statistical Monitor plays a critical role in supporting Risk-Based Monitoring within Clinical Drug Development by operating and maintaining the centralized Statistical Monitoring function. This position focuses on detecting unusual data patterns, systematic errors, and potential instances of non-compliance or fraud that may not be identified through routine monitoring processes. The Statistical Monitor analyses clinical data across trials and projects to safeguard data integrity, which is essential for the approval of new drug. The role requires a high level of independence, with the potential to mentor junior colleagues and contribute to continuous improvement in data reliability and compliance. Responsible to operate and maintain the Statistical Monitoring function to identify unusual data patterns, systematic errors, and potential protocol non-compliance or fraud across clinical trials and projects. Work closely with trial and project teams, as well as data management and programming experts, to plan and execute statistical monitoring activities according to project timelines. Communicate monitoring observations to relevant stakeholders, support the interpretation of data issues, and contribute to data correction and quality improvement efforts. Contribute to the development, maintenance, and enhancement of statistical monitoring tools and methodologies, including exploring and implementing new techniques. Support training initiatives, participate in meetings and seminars, and foster strong collaboration and knowledge sharing with colleagues and cross-functional teams. Qualifications Holds university degree in life science or engineering (e.g. B.Sc., MSc, MD) or equivalent. 2 years of experience in pharmaceutical industry and preferably 1 year of experience with exploration and/ or visualisation of clinical trial data and scientific data. Experience from clinical development and understanding of data flow. Thorough understanding of clinical research and GCP. Understanding of basic statistical methods, preferably experience from reporting/publishing clinical/scientific data. Good knowledge on computer systems and IT. Exposure with SAS / JMP programming. Worked according to GxP and guidelines within drug development.

Plan and execute advanced microbiological research to develop new products and optimise existing processes.Conduct microbial culturing, isolation, identification, and characterisation using classical and molecular biology techniques.

Work in shifts as in charge and help to run the production system in most efficient ways by utilizing full capacity and resources: Roles and Responsibilities: Overall Implementation of process management in cell line Technical Evaluation of Potential Raw Material & vendor Training & Developing of technical teams Prepare SOPs, Control Plan/WI/CS/SPC for process & their revision as per requirement Rejection analysis & suggest improvement actions Bring in the expertise in solar cell process development to increase cell efficiency/yield Continuous Improvement in cell efficiency, yield, Throughput & drive cost reduction projects Control of Non-Conforming Productions Response & Ensuring actions against Customer ComplaintsKeep up-to-date on new external developments on solar cell processesResponsible to keep a close eye on external developments in solar cell technology that might be relevant to ReNew technology roadmap Safety: Achieve zero safety incidents Comply with the company’s safety protocols at all times Participate in projects related to safety improvement Required Skills: Expert in Solar Cell Process & Technology Characterization knowledge of Solar cell for process improvement (e.g. Loss analysis, IQE-EQE, SIMS, ECV, etc.) Experience in Six Sigma Methodologies, QC tools & Statistical Software (Minitab, JMP etc.) & MS Office. Good presentation, interpersonal and communication skill Ability to gather and review resources and select and synthesize data for reports and other written materials Profile & Eligible Criteria: • 3+ years (in Solar PV Cell Process) • Minimum Bachelor degree in Engineering or Science