矿物勘探中基于机器学习的地球物理遗产数据解读博士研究生岗位

该项目致力于开发方法，利用地质历史地震数据和井录数据，结合地球化学分析与机器学习技术，来研究沉积环境中铜矿资源分布。 申请者将致力于识别与描述铜质片岩层，运用先进的数据分析技术，并依托国际研究网络开展合作研究。

Job description: We are looking for a PhD candidate who is keen to explore how legacy seismic and well-log data acquired for petroleum exploration can be transformed into a new resource for deep mineral exploration. The candidate will combine quantitative geophysical interpretation, basin modelling and machine learning to investigate a challenging target: the thin Kupferschiefer horizon buried beneath the Netherlands and the North Sea. The Dutch subsurface offers an exceptional dataset of more than 6,000 wells, including approximately 1,700 in which the Kupferschiefer has been identified, together with extensive high-quality 2D and 3D seismic reflection data and available cores. Yet these data were acquired and interpreted for hydrocarbon exploration. Recognizing and mapping a horizon a few metres thick at kilometers depth, and identifying features associated with its mineral potential, requires methods that can extract information across datasets with very different resolution, coverage and physical meaning. The goal of this PhD project is to develop an integrated methodology for characterizing the Kupferschiefer and its geological context. You will analyse well logs to identify the target horizon and extrapolate it to wells where it has not yet been recognized. You will use seismic data for cross-well correlation and improved spatial characterization, and basin analysis to investigate the roles of stratigraphy, faulting and basin evolution. Geological, petrophysical, geochemical and mineralogical information will be integrated to identify characteristics and fingerprints associated with copper mineralization. Machine learning will be an important part of this methodological development. You will establish robust and interpretable baseline models for well-log analysis and investigate approaches designed for sequential data, including convolutional and transformer-based models. You will also contribute to multimodal methods that combine seismic, well-log, geological and geochemical information while incorporating geological knowledge and physical constraints. A postdoctoral researcher will work alongside you for one year, focusing primarily on advanced multimodal and physics-informed machine-learning developments. The research is part of the EU-funded INTELLIGENT project. Results from the Dutch basin will be combined with complementary studies by other groups working on the Kupferschiefer and related systems to develop a regional-scale mineral-system model and transferable exploration workflows. Your multidisciplinary research work will be carried out within the Applied Geophysics and Petrophysics Section and the Resource Engineering Section of GSE at TU Delft. Through close collaboration with TNO, the National Materials Observatory and partners from universities, geological surveys, research institutes and industry across Europe, you will test new methodological ideas within an international network and against a real, societally relevant exploration challenge.

职位要求： 具备创新与独立精神，您能够开展自主研究，并在地球科学、工程学及数据科学领域之间进行合作。 您还需具备： 拥有地球物理学、地质学、地球科学、地质或石油工程以及相关学科的理学硕士学位。 对应用地球物理学、资源勘探及机器学习方法的兴趣。 具备科学编程经验（优先掌握 Python 或 Matlab）。 良好的写作与沟通能力。 在以下一个或多个领域具有相关经验将被视为优势： 盆地分析、盆地建模或沉积盆地演化研究。 地震反射数据及井测曲线的定量解释。 岩石物理学、低温地球化学与矿物学。 机器学习（深度学习和/或统计学习方法） 代尔夫特理工大学（代尔夫特大学） 在代尔夫特理工大学工作意味着为真正具有影响力的解决方案作出贡献。 180 多年来，我们一直培养能够在全球企业、政府机构或创业领域产生影响力的工程师。我们的校友将知识转化为应对当今与未来挑战的具体解决方案。这些挑战正在迅速变化。因此，我们每天都专注于能源、气候、数字化、人工智能（AI）和智能交通等主题。 我们的教学与研究直接契合社会当前及未来的需求。 在代尔夫特理工大学，我们的人员至关重要。凭借他们的知识与好奇心，教职员工提供高质量的教育服务，并开展超越校园范围的开创性研究。你将有机会主动担当、与他人合作，并成长为一名优秀的专业人士。在代尔夫特理工大学工作意味着加入一个由专业人士与学生组成的国际社区。我们共同创造知识、创新成果及解决方案，助力推动世界的进步。 土木工程与地球科学学院 土木工程与地球科学学院（CEG）致力于在土木工程、应用地球科学、交通与运输、水技术及三角洲技术领域开展卓越的国际研究与教育工作。我们的研究不仅服务于教育项目，还涉及气候变化、能源转型、资源供应、城市化及清洁水等社会挑战。我们的研究项目与众多研究机构紧密合作开展。CEG坚信开放科学的重要性，并支持其科学家将开放科学融入研究实践之中。 CEG学院由以下七个部门中的28个研究小组组成：材料力学管理与设计、工程结构、地球科学与工程、地球科学与遥感、交通与规划、水力学及水资源管理。 点击此处进入土木工程与地球科学学院的网站。

Conditions of employment: Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from €3204 - €4051 gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged. Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service , offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.

Application procedure: Are you interested in this vacancy? Please apply no later than 17 November 2026 via the application button and upload the following documents: Motivation letter. Curriculum Vitae, including a list of relevant courses. If applicable, the topic of your MSc thesis. You can address your application to ［会员专属信息］. Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the Graduate Schools Admission Requirements . Please note: You can apply online. We will not process applications sent by email and/or post. As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel. We do this, among other things, to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed. The processing of personal data in the context of the risk assessment is carried out on the legal basis of the GDPR: performing a public task in the public interest. You can find more information about this assessment on our website about knowledge security. Please do not contact us for unsolicited services.