Studentische Hilfskraft (w/m/d) – Forschungsdatenmanagement & IoT (in German only) [V000011551]

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title as heading. Must not include Job ID etc. Must preserve all substantive info, remove boilerplate, navigation, EEO, etc. Must not create sections with filler like "commensurate with experience". Must output only HTML fragment. We need to parse the posting: It's a student assistant (Hiwi) job: "Studentische Hilfskraft (w/m/d) – Forschungsdatenmanagement & IoT". Provide details: Provider: Lehrstuhl für Textilmaschinenbau und Institut für Textiltechnik. Profile: description of institute. Your profile: interest in digitalization, software development, data or AI applications; first experiences with Python, databases, Git or interfaces helpful but not required; topics like LLMs, knowledge management, IoT, sensorics, machine data interesting; eager to learn new technologies, work reliably, structured, enjoy teamwork; prior knowledge welcome but interest, initiative, willingness to learn more important; enrolled in a university or Fachhochschule. Tasks: participation in development of AI-based knowledge management software; support processing, structuring, integration of research data, technical documents, machine data; participation in development of data pipelines, databases, interfaces and connection of IoT systems and sensors; support development and evaluation of AI applications, e.g., LLMs, RAG, semantic search; depending on interest and prior knowledge, work in further topics like data visualization, process analysis, Lean Management or Digital Twins. Offer: employment as student assistant; position to be filled asap, limited to 12 months; extension and long-term employment sought; part-time; regular weekly working time 6 hours; can be increased after successful induction; classification according to guideline for student and scientific assistants; position evaluated at 15.20 € per hour. About us: RWTH certified family-friendly university; offers health, counseling, prevention offers via university health management (e.g., university sports); for tariff employees and civil servants extensive training and possibility to obtain job ticket; posting addresses all genders; additionally, all employees have access to Corporate Benefits platform with discounts; want to promote careers of women; women preferred if underrepresented; applications of severely disabled persons expressly desired; ask to omit application photo; link to DSGVO info. Application details: deadline 22.12.2026; contact Sven Gores; address; email; phone; etc. But we must remove application instructions? The instruction says: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we should drop the "Bewerbungsfrist: 22.12.2026 Jetzt bewerben" etc? Actually "application instructions" includes things like "Bewerbung Nummer V000011551", postal address, email, phone, "Jetzt bewerben". We should drop those. Also drop EEO statements about women preference, disabled persons, etc. Also drop corporate benefits, health offers maybe considered boilerplate? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "Über uns" section includes some info about RWTH being family-friendly, health offers, corporate benefits, women promotion, disabled persons, etc. Some of that might be considered EEO/boilerplate. However, we need to preserve ALL substantive information; do NOT invent or summarize away detail. The "Über uns" includes substantive info about RWTH being family-friendly, health offers, corporate benefits, women promotion, disabled persons. Are those considered EEO/boilerplate? They are about equal opportunity and benefits. The instruction says remove EEO/equal-opportunity/scam-warning boilerplate. So we should remove those lines. However, the "Über uns" also includes "Die RWTH ist als familiengerechte Hochschule zertifiziert. Die RWTH bietet im Rahmen eines Universitären Gesundheitsmanagements eine Vielzahl von Gesundheits-, Beratungs- und Präventionsangeboten (z. B. Hochschulsport) an." That could be considered benefits? Might be considered benefits section. But we need to decide: The instruction says remove EEO/equal-opportunity/scam-warning boilerplate. The part about family-friendly certification and health offers could be considered benefits. However, they also mention corporate benefits platform with discounts. That is a benefit. The women preference and disabled persons are EEO. So we should strip those. Thus we keep substantive info: About the role (maybe a brief description of the institute and the role). Responsibilities (tasks). Requirements/Qualifications/Skills (your profile). Benefits (maybe the hourly wage, part-time, possibility to increase hours, 12-month contract, extension sought). Pay (hourly wage 15.20 €). Schedule (weekly working time 6 hours, can be increased). Also maybe "About us" could be considered "About the role" or "About the institute". We'll create sections: About the role (description of institute and role). Responsibilities (list of tasks). Requirements (list of profile items). Qualifications (maybe same as requirements? Could combine). But we need to avoid thin sections. Better to combine Requirements and Qualifications into one? But the instruction says use headings for those categories if they have content. We can have Requirements and Qualifications separate if we have distinct content. However, the posting lumps interest, experience, topics, motivation, teamwork, prior knowledge, enrollment. That's more like qualifications/skills. We could put Requirements as "Enrolled in a university or Fachhochschule". Qualifications as "Interest in digitalization, software development, data or AI applications; first experiences with Python, databases, Git or interfaces helpful but not required; topics like LLMs, knowledge management, IoT, sensorics, machine data interesting; eager to learn new technologies, work reliably, structured, enjoy teamwork; prior knowledge welcome but interest, initiative, willingness to learn more important". Skills could be "Python, databases, Git, interfaces, LLMs, knowledge management, IoT, sensorics, machine data, data visualization, process analysis, Lean Management, Digital Twins". But we need to avoid duplication. Better: Use sections: About the role (institute description and role). Responsibilities (tasks). Requirements (enrollment). Qualifications (interest/experience). Skills (specific technologies). Benefits (contract type, duration, extension prospect, corporate benefits? but we removed corporate benefits). Pay (hourly wage). Schedule (weekly hours). However, we need to check if we have enough content for each. Let's extract: About the role: The institute develops textile machines, components, innovative materials, novel procedures for textile production; focus on digitization of production processes in nonwoven and paper industry; aim: development of data-driven production and research processes; process and quality data systematically captured, structured, evaluated, made usable for further applications; modern IoT architectures, sensorics, databases, digital process twins, concepts of research data management; another focus: development of AI-supported knowledge management software to structure technical knowledge, research data, documents, test results for employees and research projects; using LLMs, RAG, semantic search, modern software architectures. That's substantive. Responsibilities: list tasks as bullet points. Requirements: "Du bist für ein Studium an einer Hoch- oder Fachhochschule eingeschrieben". That's a requirement. Qualifications: "Du hast Interesse an Digitalisierung, Softwareentwicklung, Daten oder KI-Anwendungen; Erste Erfahrungen mit Python, Datenbanken, Git oder Schnittstellen sind hilfreich, aber keine Voraussetzung; Themen wie Large Language Models, Wissensmanagement, IoT, Sensorik oder Maschinendaten findest du spannend; Du hast Lust, dich in neue Technologien und Fragestellungen einzuarbeiten und eigene Ideen einzubringen; Du arbeitest zuverlässig und strukturiert und hast Freude an der Zusammenarbeit im Team; Vorkenntnisse in einzelnen Bereichen sind willkommen, wichtiger sind uns Interesse, Eigeninitiative und die Bereitschaft, Neues zu lernen". That's qualifications. Skills: Could be derived from qualifications: Python, databases, Git, interfaces, LLMs, knowledge management, IoT, sensorics, machine data, data visualization, process analysis, Lean Management, Digital Twins. But those are more topics of interest. Might be better to put them under Qualifications. However, we need to avoid thin sections. Perhaps we combine Qualifications and Skills into one section "Requirements & Qualifications". But the instruction says use headings for those categories if they have content. It doesn't forbid combining, but we should follow the headings list. We could have Requirements and Qualifications separate, but Skills maybe thin. We could omit Skills if not enough distinct content. The instruction: "Prefer a few substantive sections over many thin ones." So we could combine Requirements and Qualifications into one section called "Requirements" (or "Qualifications") and not have Skills separate. But we need to use the allowed headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We can choose to include only those with real content. So we could include About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule. Omit Skills if not enough distinct content. Now Benefits: The posting mentions: "Die Einstellung erfolgt als Studentische Hilfskraft. Die Stelle ist zum nächstmöglichen Zeitpunkt zu besetzen und befristet auf 12 Monate. Grundsätzlich wird eine Verlängerung und eine langfristige Anstellung angestrebt. Es handelt sich um eine Teilzeitstelle. Die regelmäßige Wochenarbeitszeit beträgt 6 Stunden. Die Wochenarbeitszeit kann nach erfolgreicher Einarbeitung erhöht werden. Die Eingruppierung richtet sich nach der Richtlinie für studentische und wissenschaftliche Hilfskräfte. Die Stelle ist bewertet mit 15,20 € pro Stunde." Also mentions RWTH family-friendly certification, health offers, corporate benefits, but those are EEO/benefits maybe we should keep benefits like contract type, duration, extension prospect, part-time, hourly wage, possibility to increase hours. However, Pay and Schedule are separate headings. So Benefits could include: employment as student assistant, start asap, 12-month contract, extension sought, part-time, classification according to guideline, maybe also mention of family-friendly certification? That might be considered benefits but could be EEO. Safer to include only substantive non-EEO benefits: contract type, duration, extension prospect, part-time, possibility to increase hours, classification per guideline. That's enough. Pay: hourly wage 15,20 €. Schedule: regular weekly working time 6 hours, can be increased after induction. Now we need to format: Use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We must not repeat job title as heading. So no heading for "Studentische Hilfskraft (w/m/d) – Forschungsdatenmanagement & IoT". We'll just start with sections. We must not put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it. We'll drop the application metadata. We must preserve ALL substantive information; do NOT invent or summarize away detail. So we need to include all details from the posting that are not boilerplate. Let's list all substantive info: - Institute description: develops textile machines and components, innovative materials, novel procedures for textile production; special focus on digitization of production processes in nonwoven and paper industry; goal of current research projects: further development of data-driven production and research processes; process and quality data systematically captured, structured, evaluated, made usable for further applications; modern IoT architectures, sensorics, databases, digital process twins, concepts of research data management; another focus: development of AI-supported knowledge management software to structure technical knowledge, research data, documents, test results for employees and research projects; using LLMs, RAG, semantic search, modern software architectures. - Your