人工智能 数据科学方向全奖[高薪]博士职位机会速递：自动驾驶、网络安全、气候管理等方向

人工智能 数据科学方向全奖[高薪]博士职位机会速递：自动驾驶、网络安全、气候管理等方向

（1）PhD position Data-Efficient Deep Learning for Autonomous Driving

Job description

The Intelligent Vehicles (IV) group at TU Delft (*) is seeking a PhD candidate with an interest in performing cutting edge research in the area of environment perception for self-driving vehicles. This PhD position is part of a new EU project EVENTS (ReliablE in-Vehicle pErception and decisioN-making in complex environmenTal conditionS) containing several automotive industry and research partners across Europe.

The PhD position addresses data-efficient deep learning for autonomous driving. Existing datasets are often manually labeled by human annotators and state-of-the-art methods use fully supervised techniques to learn from these datasets. The goal of this position is to develop methods that use unsupervised/semi/self-supervised learning, domain adaptation, active learning and prior knowledge to reduce the amount of labeled data that is needed. We perform multi-modal environment perception (i.e. using vision, radar and lidar) in urban traffic scenarios, with a special focus on Vulnerable Road Users (pedestrians, cyclists and other riders).

The Intelligent Vehicles group at TU Delft brings together world- class researchers from perception, prediction, control and human factors research. Our intelligent vehicle platform is regularly used to showcase our technology to the public.

Requirements

Applicants should have (or soon expect) a Master Degree in a relevant discipline (e.g. Computer Science, Electrical/Mechanical Engineering, Artificial Intelligence, Robotics). They should have a strong academic record with a solid background in computation, sensor processing (e.g. computer vision), machine learning and AI. Good programming skills are expected, preferably in C++ and/or Python. Knowledge of deep-learning frameworks (TensorFlow/PyTorch/Keras/Caffe) and OpenCV/ROS/CUDA is a plus. A certain affinity towards turning complex concepts into real-world practice (i.e. vehicle prototype) is desired. Applicant(s) are expected to be able to act independently as well as to collaborate effectively with members of a larger team. Good English skills are required.

截止日期1 August 2022

（2）PhD Positions in Data-driven Cybersecurity

Job description

The Cybersecurity (CYS) group at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) invites applications for full-time doctoral candidates in the area of Data-driven Cybersecurity. Successful candidates will follow a data-driven approach by collecting and analyzing massive network and web data to improve security and privacy in the Internet. Examples include fighting cyber threats (e.g., ransomware, phishing, denial of service attacks, scanning for system vulnerabilities), identifying and mitigating network and Web vulnerabilities (e.g., unauthorized access, user tracking), and assessing the adoption of user data protection regulations (e.g., GDPR) in the wild. Successful candidates will have the opportunity to work closely with world- class researchers at TU Delft and our research collaborators in Europe and the US.

Our group conducts research in a range of cybersecurity topics, including, secure data analytics, applied cryptography, privacy, cloud security, system security, and network security. We aim to make the world a safer place as most of our activity and data move online. We design, develop, and evaluate interdisciplinary solutions that combine all fields of computer sciences: artificial intelligence, systems, and theory. Examples include the development of deep learning methods that are immune to common side-channel defences, machine learning algorithms that can operate on encrypted data in the cloud, detection and mitigation of large scale distributed denial of service attacks, and analysis of the latest security threats. We aim to publish our results at top conferences and journals, transfer our scientific know-how and technologies to students and our public and private partners in the field of cybersecurity, and have impact in society and the research community.

Requirements

截止日期 September 15, 2022

（3）PhD Position on Artificial Intelligence for Collaborative Climate Risk Management

Job description

Climate changes, such as sea level rise, soil subsidence, extreme rainfall, and drought, induce new challenges and risks for real estate and infrastructures, especially in low lying urbanized deltas, as in the Netherlands. While people’s homes, communities, and livelihoods are at stake, real estate climate risks also stand to destabilize markets and society at large. Climate risk management requires collaborative, integrated strategies that cut across public, private, and civic spheres to achieve societal impact.

Your goal, in this PhD project, is to develop Artificial Intelligence (AI) techniques for supporting an Integrative Forum (IF), which facilitates two-way exchange and knowledge co-creation on climate risk management. The IF, on the one hand, provides a ‘soft space’ for debate and reflection between research teams, societal partners, and citizens at large. On the other hand, the dialogue in the IF provides an opportunity for innovative research on institutionalized logics, tactics, and procedures that hinder or enable effective cross-disciplinary collaboration.

AI (e.g., natural language processing, and knowledge representation and reasoning) techniques can support the IF by, for example, recognizing the stakeholders’ values and norms, clustering and visualizing stakeholders’ arguments and perspectives, identifying disagreements, finding novel viewpoints, and modelling opinion dynamics over time.

The data for AI techniques comes from the recordings and transcripts (obtained with appropriate permissions) of the meetings in the forum, which will be organized regularly during the project. Further, where available, we can employ discursive data outside the forum, e.g., on social and news media.

You will address the following preliminary research objectives, which will be refined by you in cooperation with your supervision team.

Generate cross-disciplinary research insights and build collective governance capacity through dialogue, reflection, and mutual learning facilitated within the Integrative Forum and other ‘soft spaces’ of the consortium.

Leverage AI to draw out stakeholders’ institutionalized logics, tactics and procedures in order to facilitate cross-consortium reflection and learning and build collective governance capacity.
Create generalizable institutional and strategic insights about how to enable productive two-way transdisciplinary and cross-actor exchanges which build capacity for integrated climate risk management in the built environment, and which can be leveraged in comparable urban regions in the Netherlands and beyond.

This PhD position is part of Work Package 5 (WP5) of the R eal E state D evelopment & B uilding in L ow U rban E nvironments ( RED&BLUE ) research initiative, a major new program funded by the Dutch Research Council. This initiative aims to develop transdisciplinary knowledge on climate resilient real estate and infrastructure development. More information can be found at: www.redblueclimate.nl. In addition to you, WP5 involves a postdoctoral researcher, with whom you will closely collaborate.

As a member of the RED&BLUE team, you will do high-impact research on a pressing societal topic relevant within the Netherlands and beyond. Your research will enable you to actively collaborate with other researchers and societal partners, providing you with exceptional mentorship, personal development, and networking opportunities. You will also build upon the work of other researchers and real-world urban use cases. For this reason, we also emphasize that international PhD candidates should be willing to learn Dutch to at least B1/B2 level after one year.

Requirements

The candidate must have:

Completed an MSc degree in Artificial Intelligence, Computer Science, or another field relevant to the PhD topic, e.g., Spatial Planning, with completed AI, Computer Science, or related courses.

Demonstrated competence or strong interest in a relevant artificial intelligence topic such as natural language processing, social computing, or multiagent systems.

Strong programming skills.

Excellent spoken and written English, required for scientific publishing. If your native language is not English and you do not hold a degree from an institution in which English is the language of instruction, you must submit proof of English proficiency from either TOEFL (minimum total score of 100) or IELTS (minimum total score of 7.0).

A good command of the Dutch language, considering the consortium members and case studies of this research as well as the societal dissemination of your results to Dutch audiences. If the candidate does not speak Dutch, (s)he should be willing to learn Dutch as the first priority, and we expect the candidate to reach the Dutch B1/B2 language level within one year.

Excellent communication skills and the ability to switch between operational and managerial levels within the various disciplines that are part of this research.

Team spirit and an open personality, particularly for cooperation with colleagues across disciplines and for co-supervision of students.

截止日期 August 5, 2022

注意这些机会对英语要求较高 雅思7 托福100

较为统一的申请文书要求

CV

Motivation Letter

Publication list [Writing sample]

2-3 RL

[个别要求Github Profile 和/或coding project sample]

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