{"id":4168538,"url":"https://alion.io/job/siemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data","title":"PhD Thesis: Physics-Informed Predictive Models for Engineering Systems using Simulation and Sensor Data","company":{"id":131,"name":"Siemens","domain":"siemens.com","url":"https://alion.io/company/siemens","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Avature","truth_index":{"grade":"A","score":100,"open_postings":34,"ghost_share":0,"stale_share":0,"repost_share":0.029,"time_to_fill_p50_days":15,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Early Careers","role_family":"Early Careers","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Garching bei München, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false}],"status":"live","first_seen_at":"2026-11-12T14:00:42Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-13T03:23:35Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Mode of Employment: Fixed Term / Part-Time; (20 hours / week)\nAre you passionate about merging physics, machine learning, and engineering to shape the future of predictive modeling? Join us in Garching as a PhD candidate (f/m/d) and drive innovation at the intersection of simulation, sensor data, and AI for next-generation engineering systems!\nWhat we offer you\n Attractive remuneration package\n 30 leave days and a variety of flexible working models that allow time off for yourself and your family\n Share matching programs to become a shareholder of Siemens AG\n Continuous Learning: Benefit from specialized training and daily challenges to keep your expert knowledge up-to-date\n Innovative Environment: Be part of a team that values innovation and continuous improvement\n Since each of over 300,000 employees feels that other benefits are particularly important, and we cannot list our entire benefit portfolio here, you can find more information here.\n The individual benefits are subject to regulatory, contractual, or corporate conditions.\nYou'll make an impact by\nYou develop physics-informed predictive models that combine simulation data with real-world sensor inputs to accurately represent complex engineering systems\nBuilding on this, you implement fast surrogate and reduced-order models to enable efficient simulations and analyses\nYou investigate advanced machine learning methods such as Neural Operators and Operator Inference, with the aim of improving model generalization and performance\nAdditionally, you address the challenges of transferring models from simulation to real-world applications (Sim2Real), ensuring robust performance even with noisy, sparse, or incomplete sensor data\nTo ensure reliability, you integrate uncertainty quantification (UQ) methods into your models, providing trustworthy and interpretable predictions\n This is how you'll win us over\nEducation: You hold a Master’s degree in a relevant field such as mathematics, engineering, physics, or computer science.\nExperience and Skills:You have experience with physics-informed predictive modeling for engineering systems\nYou are skilled in combining simulation and sensor data, including handling noisy, sparse, and incomplete datasets\nYou possess knowledge of neural operators, operator inference, and uncertainty quantification for reliable predictions\n\nWays of Working: You work analytically, independently, and demonstrate strong problem-solving abilities\nLanguages: Very good English skills are required, German is recommended\n You are much more than your qualifications, and we believe in the potential of every single candidate. We look forward to getting to know you!\n At Siemens, we believe that feeling valued and included is the foundation for doing great work. That’s why we aim to create an inclusive workplace where everyone feels a sense of belonging, and where individual perspectives and experiences are celebrated. Our commitment to fairness and respect extends to every applicant. As an equal opportunity employer, we welcome applications from individuals of all backgrounds and particularly encourage applications from persons with disabilities.\nAbout Us \nThe world never stands still. And new challenges arise every day. With a passion for questioning things, for supplying ideas, and intelligently driving things forward we are helping society move towards a smarter tomorrow. Be it with technologies that reduce carbon emissions in cities or hyperintelligent robots. This is how we are able, to tackle the most important projects and push them forward together. Help us shape the future.\nwww.siemens.de/careers - if you would like to find out more about jobs & careers at Siemens.\n FAQ - if you need further information on the application process.","description_format":"text","description_chars":3766,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[{"language":"German","level":"All levels","optional":false},{"language":"English","level":"All levels","optional":false}]},"benefits":["Continuous learning","Flexible schedule"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["CAD, PLM & BIM Software","Rail Transport","Building Automation & Controls","Manufacturing & Industrial Software"],"lifecycle":[{"event":"open","at":"2026-11-12T14:00:42Z"}],"visa":[],"liveness":{"score":86,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.86,"p_room":1,"age_days":0,"expected_fill_days":15,"reasons":["conf:3","win:early","comp:brand"],"computed_at":"2026-11-13T06:56:20Z"},"pay":null,"html_url":"https://alion.io/job/siemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data","json_url":"https://alion.io/job/siemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data.json","meta":{"generated_at":"2026-11-13T06:56:20Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":14565,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-14T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.1,"usd":0.01,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":131},"rest":"https://alion.io/mcp/rest/get_company?id=131"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsiemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"free","price":{"credits":0,"usd":0},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fsiemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.1,"usd":0.01},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fsiemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/siemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsiemens-phd-thesis-physics-informed-predictive-models-for-engineering-systems-using-simulation-and-sensor-data"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":4168538}},{"tool":"search_jobs","arguments":{"company":"siemens.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":4168538},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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