高效长上下文视觉与视觉-语言-动作系统大模型博士研究员(科研助理,TV-L 13)
PhD Position - Efficient Long-Context Large Models for Vision and Vision-Language-Action Systems (f/m/d)
原帖优先:申请材料、截止时间与资格以原帖和学校官方说明为准。
AI 中文速览
- 研究内容
- 你将研究用于计算机视觉和视觉-语言-动作(VLA)系统的高效长上下文模型,并将其应用于自动驾驶。研究将结合注意力优化、token缩减、模型剪枝和量化,在保持准确性、鲁棒性和下游动作质量的同时实现大模型的可扩展性。
- 申请条件
- 申请者需持有工程学、计算机科学、机器人学或相关领域的优秀硕士学位;具备深度学习和大模型架构的扎实知识;拥有深度学习软件开发经验;对独立开展科学研究充满兴趣,并热切希望积极参与优秀的国际化团队。
- 待遇
- 薪资按 TV-L 13 档次发放(年薪约 59300 至 63600 欧元);合同期限为 3 年;提供结构化入职培训、持续进修机会、灵活工作时间、远程办公选项、30天带薪年假、“KIT-Family +”家庭友好支持项目、健康健身及心理健康项目、VBL 企业年金以及 JobTicket BW 每月 25 欧元补贴。
- 申请方式
- 原文未说明具体提交网址、语言或文件格式要求,请通过公告中的联系方式或招聘系统在 2026-11-08 前提交申请。
由 gemini-2.5-flash-lite 生成,博士岗判定置信度 100%。
岗位信息
- 截止
- (Europe/Berlin) 剩 23 天
- 学科
- 计算机科学
- 合同类型
- 雇佣合同
- 合同期限
- 3 年
- 原文薪资
- EUR 59,300–63,600 / 年(税前)
- 原帖发布
- 本站收录
- 内容更新
- 原帖导师候选(待核验)
- Dr. Martin Lauer
- 来源
- Karlsruher Institut für Technologie 官方招聘 · 最近核对 2026-10-15
- 详情核验
薪资与生活预算(估算)
- 税前月薪
- 约 EUR 4,942–5,300 / 月
- 税后月薪(情景估算)
- 约 EUR 3,262–3,498 / 月 ≈ ¥25,768–27,634 / 月
按税前扣除 34% 试算,包含所得税与雇员社保的简化预算;不代表个人实际税率。
- 月租预算
- EUR 550 / 月(比较情景,非所在城市或德国平均租金)
- 扣房租后(估算)
- 约 ¥21,423–23,289 / 月
仅减房租,尚未扣除食品、交通、水电等其他生活费。
计算依据与调整预算
单身、无子女、无教会税的比较情景;34%为本站假设,不是税级I的固定税率或完整德国工资税计算。实际扣除取决于税级、医保、社保及补充养老等。 德国财政部工资税计算器 ↗只计算相关税额,社保等需另计。
税后 = 税前 ×(1 − 扣除比例);人民币 = 税后欧元 × 汇率;房租后 =(税后欧元 − 房租)× 汇率。汇率 7.9 为情景输入,未核验为实时牌价,房租 550 欧元为预算假设。
参数只在当前页面试算,不上传服务器,不改变原帖数据。
判定依据(原文摘录)
- 该职位为博士培养机会
PhD Position - Efficient Long-Context Large Models for Vision and Vision-Language-Action Systems (f/m/d)
- 工作语言为英语且不需要本地语言
eagerness to actively participate in a great international team.
- 要求硕士学位而非学士学位
an excellent Master’s degree in engineering, computer science, robotics or similar
原文
For more than one decade the Institute of Measurement and Control Systems (MRT) at KIT has been one of Germany’s leading autonomous driving labs. Its unique advantage is the availability of experimental vehicles with sensors, actuators and a complete software stack for automated urban driving. The existing equipment and experience not only enables continuous cutting-edge research in all areas of autonomous driving, but also a wide range of collaborations with leading industrial partners. Research highlights of the MRT are, among others, the successful participation in autonomous driving competitions as well as the development of highly influential benchmark suites like KITTI and KITScenes.
Your Tasks Large foundation models and vision-language-action models increasingly rely on long context windows to reason over high-resolution images, videos, multi-camera sensor streams, maps, interaction histories and language instructions. However, standard attention mechanisms scale unfavorably with context length, and large models remain difficult to deploy under real-time, memory and energy constraints in autonomous systems. You will investigate efficient long-context models for computer vision and VLA systems and apply it to autonomous driving. The research will combine attention optimization, token reduction, model pruning and quantization to make large models scalable while preserving accuracy, robustness, and downstream action quality. The research will build on established ideas from Transformers, long-sequence attention, memory-efficient attention, vision transformers, deep compression, and recent VLA systems.
Your Profile You are a dedicated and creative person with • an excellent Master’s degree in engineering, computer science, robotics or similar • proven knowledge of deep learning and large model architectures • experience in software development for deep learning • interest in working independently and scientifically, and • eagerness to actively participate in a great international team.
We Offer
Science for Impact
Engage with topics of societal relevance — in an excellent scientific environment that enables change.
Career‑Building and Developmental Opportunities
We provide you with a structured onboarding program, a broad spectrum of continuing‑education options, and personalised support, thereby fostering your individual growth.
Flexible Working Hours
Take advantage of flexible‑hours schemes, remote‑work options, and a 30‑day annual leave entitlement to achieve an optimal work‑life balance.
Family-friendliness
The “KIT‑Family +” program assists you in reconciling work and family life by offering childcare services, holiday activities, a parent‑child office space, and assistance with caring for relatives.
Stay Healthy
Under the motto “Fit at KIT – Body, Mind and Soul,” we promote your well‑being through fitness classes and mental‑health programmes.
Individualised Extra Benefits
Enjoy a corporate pension (VBL), a €25 monthly contribution toward a JobTicket BW, plus a broad selection of cultural and recreational programmes.
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• Science for Impact : Engage with topics of societal relevance — in an excellent scientific environment that enables change.
• Career‑Building and Developmental Opportunities : We provide you with a structured onboarding program, a broad spectrum of continuing‑education options, and personalised support, thereby fostering your individual growth.
• Flexible Working Hours : Take advantage of flexible‑hours schemes, remote‑work options, and a 30‑day annual leave entitlement to achieve an optimal work‑life balance.
• Family-friendliness : The “KIT‑Family +” program assists you in reconciling work and family life by offering childcare services, holiday activities, a parent‑child office space, and assistance with caring for relatives.
• Stay Healthy : Under the motto “Fit at KIT – Body, Mind and Soul,” we promote your well‑being through fitness classes and mental‑health programmes.
• Individualised Extra Benefits : Enjoy a corporate pension (VBL), a €25 monthly contribution toward a JobTicket BW, plus a broad selection of cultural and recreational programmes.
Job location Karlsruhe (and Eggenstein-Leopoldshafen)
Salary Salary category 13 TV-L; classification is based on personal and professional qualifications. Contract duration 3 years
Contact person in line-management Dr. Martin Lauer martin.lauer@kit.edu
If you have general questions about the application process, please contact Julia Boldt Personalservice (PSE) julia.boldt@partner.kit.edu
At KIT we value the diversity of our employees; different perspectives and backgrounds enrich our work. We therefore welcome applications from all candidates. Women are especially encouraged to apply. Applications from recognized severely disabled individuals are given preferential consideration when qualifications are equal. Application up to: 2026-11-08 Job posting number: 1252/2026