6 Coq Jobs

The job involves designing architectures for meta-learning, self-reflective agents, and recursive optimization loops. Building simulation frameworks grounded in Bayesian dynamics, attractor theory, and teleo-dynamics. Developing systems that integrate graph rewriting, knowledge representation, and neurosymbolic reasoning. Researching fractal intelligence structures, swarm-based agent coordination, and autopoietic systems. Advancing Mobius's knowledge graph with ontologies supporting logic, agency, and emergent semantics. Integrating logic into distributed decision graphs aligned with business and ethical constraints. Publishing cutting-edge results and mentoring contributors in reflective system design and emergent AI theory. Building scalable simulations of multi-agent ecosystems within the Mobius runtime. You should have a Ph.D. or M.Tech in Artificial Intelligence, Cognitive Science, Complex Systems, Applied Mathematics, or equivalent experience. Proven expertise in meta-learning, recursive architectures, and AI safety. Strong knowledge of distributed systems, multi-agent environments, and decentralized coordination. Proficiency in formal and theoretical foundations like Bayesian modeling, graph theory, and logical inference. Strong implementation skills in Python, additional proficiency in C++, functional or symbolic languages are a plus. A publication record in areas intersecting AI research, complexity science, and/or emergent systems is required. Preferred qualifications include experience with neurosymbolic architectures, hybrid AI systems, fractal modeling, attractor theory, complex adaptive dynamics, topos theory, category theory, logic-based semantics, knowledge ontologies, OWL/RDF, semantic reasoners, autopoiesis, teleo-dynamics, biologically inspired system design, swarm intelligence, self-organizing behavior, emergent coordination, distributed learning systems like Ray, Spark, MPI, or agent-based simulators. Technical proficiency required in Python, preferred in C++, Haskell, Lisp, or Prolog for symbolic reasoning. Familiarity with frameworks like PyTorch, TensorFlow, distributed systems like Ray, Apache Spark, Dask, Kubernetes, knowledge technologies including Neo4j, RDF, OWL, SPARQL, experiment management tools such as MLflow, Weights & Biases, GPU and HPC systems like CUDA, NCCL, Slurm, and formal modeling tools like Z3, TLA+, Coq, Isabelle. Core research domains include recursive self-improvement and introspective AI, graph theory, graph rewriting, knowledge graphs, neurosymbolic systems, ontological reasoning, fractal intelligence, dynamic attractor-based learning, Bayesian reasoning, cognitive dynamics, swarm intelligence, decentralized consensus modeling, topos theory, autopoietic system architectures, teleo-dynamics, and goal-driven adaptation in complex systems.,

Role & responsibilities Involves preparation of Pricing files & Documentation extraction support. • Update Prices on SAP with different prices conditions (Flex or Fixed prices) • Extraction of data from SAP and creation of custom Price Files using MS-Access. • Price file validation to analyze Price discrepancy. Restricted - External • Oligos conditions loading to SAP. • Extraction of certificates from SAP/Websites/internal portals like SDS, COA, COO, COQ and Delivery note & Regulatory activities etc. • Real-time data exchange of Chemical Certificates to the customers. • Ability to communicate at different Level with good command over English Language. • 0 - 2 Years of experience • Experience in handling huge data & product documentation process. • Working knowledge of MS-Access, MS-Excel • Good data Analysis skills • Limited Interpersonal, Problem Solving, Planning & Execution and Impactful Communication skills. . Education / Qualifications required • B.Sc./M.Sc, B.CA/M.CA or B. Tech with strong life sciences background and proficient analytical skills in VBA, SQL, Power Automate, Python, and related tools.

JOB DESCRIPTION SUMMARY: Owns Quality of value stream, compliance, internal audits, zero defect initiative, customer issue resolution (problem solving), customer satisfaction (NPS), and CoQ governance. Manages local QMS (quality management system) to ensure the continuous production of products consistent with established standards. Coaches, supports, instructs, and ensures the commitment of local management to operate at a high level of capabilities effectively. Follows company safety policies and procedures. ESSENTIAL DUTIES: Demonstrate leadership in communicating business goals, programs, and processes for various business functions. Utilize your experience or expertise to solve problems, develop and execute objectives for yourself and others. Support regulatory compliance and optimization of quality systems procedures relating to product complaint handling, adverse event reporting, and product field actions through the development, maintenance, and improvement of documented processes. Develop and implement quality metrics to drive manufacturing improvements and business results. Facilitate shop floor process improvement projects to reduce defect occurrence. Contact customers and liaise with SQE when necessary to confer on specific quality issues Identify, drive, mentor, and implement projects improving production quality. Work with the Technical Improvement and Operations team to drive process changes Responsible for the Quality of all in-house manufactured products Drive Lean effort within manufacturing, focusing on Quality MINIMUM REQUIREMENTS Drive Change. Strong organizational, analytic, and problem-solving skills. Ability to work in cross-functional teams in a matrix environment with all levels of personnel Strong working knowledge of Manufacturing and Quality operations. Demonstrated oral and written communication skills Strong interpersonal and leadership skills Ability to plan, prioritize, and manage multiple priorities under tight deadlines Ability to coach, manage, change and facilitate team performance Education & Knowledge: Degree from an accredited university preferred. Bachelor's degree in Mechanical engineering, Quality or a related field. ASQ certification in quality management is preferred. Knowledge and applications experience with ISO 9001 (International Standard Organization), API Standards and Quality Management Systems. Working knowledge and training in the ISO-9000 Series international standards, or equivalent. Basic knowledge of audit and audit Reporting requirements. Knowledge of the process approach, including audit methodology, questioning techniques, roles, and responsibility to collect and analyse evidence. Familiarity with standard concepts, practices, and procedures within oil & gas manufacturing and services is preferred. Sound understanding of business linkages and the ramifications that decisions can have. Work Experience: Typically, at least five years of progressively more responsible experience in a manufacturing environment. Experience in a similar industry (Oil & Gas) is desired.

You will be responsible for designing architectures for meta-learning, self-reflective agents, and recursive optimization loops. Your role will involve building simulation frameworks for behavior grounded in Bayesian dynamics, attractor theory, and teleo-dynamics. Additionally, you will develop systems that integrate graph rewriting, knowledge representation, and neurosymbolic reasoning. Conducting research on fractal intelligence structures, swarm-based agent coordination, and autopoietic systems will be part of your responsibilities. You are expected to advance Mobius's knowledge graph with ontologies supporting logic, agency, and emergent semantics. Integration of logic into distributed, policy-scoped decision graphs aligned with business and ethical constraints is crucial. Furthermore, publishing cutting-edge results and mentoring contributors in reflective system design and emergent AI theory will be part of your duties. Lastly, building scalable simulations of multi-agent, goal-directed, and adaptive ecosystems within the Mobius runtime is an essential aspect of the role. In terms of qualifications, you should have proven expertise in meta-learning, recursive architectures, and AI safety. Proficiency in distributed systems, multi-agent environments, and decentralized coordination is necessary. Strong implementation skills in Python are required, with additional proficiency in C++, functional, or symbolic languages being a plus. A publication record in areas intersecting AI research, complexity science, and/or emergent systems is also desired. Preferred qualifications include experience with neurosymbolic architectures and hybrid AI systems, fractal modeling, attractor theory, complex adaptive dynamics, topos theory, category theory, logic-based semantics, knowledge ontologies, OWL/RDF, semantic reasoners, autopoiesis, teleo-dynamics, biologically inspired system design, swarm intelligence, self-organizing behavior, emergent coordination, and distributed learning systems. In terms of technical proficiency, you should be proficient in programming languages such as Python (required), C++, Haskell, Lisp, or Prolog (preferred for symbolic reasoning), frameworks like PyTorch and TensorFlow, distributed systems including Ray, Apache Spark, Dask, Kubernetes, knowledge technologies like Neo4j, RDF, OWL, SPARQL, experiment management tools like MLflow, Weights & Biases, and GPU and HPC systems like CUDA, NCCL, Slurm. Familiarity with formal modeling tools like Z3, TLA+, Coq, Isabelle is also beneficial. Your core research domains will include recursive self-improvement and introspective AI, graph theory, graph rewriting, and knowledge graphs, neurosymbolic systems and ontological reasoning, fractal intelligence and dynamic attractor-based learning, Bayesian reasoning under uncertainty and cognitive dynamics, swarm intelligence and decentralized consensus modeling, top os theory, and the abstract structure of logic spaces, autopoietic, self-sustaining system architectures, and teleo-dynamics and goal-driven adaptation in complex systems.,

We are looking for Buyer in SCM (Supply Chain Management) with minimum 3 years of experience in Oil & gas Offshore Projects. Buyer will carry out processing of RFQs, placement of orders & close out of the Purchase orders.

We're seeking PhD/MSc mathematicians with Lean (or similar) theorem prover experience to design and solve complex math problems, create clear solutions, and help evaluate AI models. LaTeX & visualization tools.Lean Tools Related to mathematics field.