This position is posted from an outside job board or employer website for the convenience of Yale students. Please note this position was not posted directly at Yale by the employer, and therefore the employer has not reviewed or agreed to any of Yale’s recruiting policies: https://ocs.yale.edu/ocs-policies/. The University does not endorse or recommend employers, and a posting does not constitute an endorsement or recommendation. The University makes no representations or guarantees about job listings or the accuracy of the information provided by the employer. The University is not responsible for safety, wages, working conditions, or any other aspect of off-campus employment. It is the responsibility of students to perform due diligence in researching employers when applying for or accepting opportunities.
The Mandiant Data Science team develops innovative, data-driven solutions to today’s most challenging cybersecurity problems. By leveraging data derived from our company’s unparalleled view of the threat landscape, the team provides solutions with significant impact for our customers and the broader cybersecurity industry. At the same time, we work on cutting-edge research at the intersection of security and machine learning. Team members have published papers and served on program committees for IEEE S&P, USENIX Security, CCS, ICML, and NeurIPS to name a few.? We actively encourage research projects that solve real-world security problems in new and exciting ways. What you will do: Our team is looking for talented interns to join us in the Reston, VA office.??We work on a variety of challenging problems across the attack life cycle, ranging from the detection of malware, fileless attacks, and exfiltration, to threat intelligence and social media analysis.? During your 12-week internship period, you will be paired with a mentor to develop a proof-of-concept machine learning system leading to a scientific publication and/or patent application.??Potential projects include: NLP and deep learning techniques to code analysis problems, such as exploit detection Knowledge graph embeddings to characterize relationships among threat actors Weak supervision methods for automated threat hunting Exploring adversarial machine learning attacks against cybersecurity models The ideal candidate for the position will be a self-motivated graduate student with the ability to both understand deeply complex technical concepts and to communicate those concepts to a diverse team of machine learning and computer security experts, in both written and verbal form.? The candidate should have previous experience working on advanced research projects with typical tools used in the academic and industrial research community, such as LaTeX and GitHub.? The candidate will gain valuable exposure to new machine learning technologies, an exciting array of real-world data, and interesting new problems, but also build their C.V. with tangible outcomes, like peer-reviewed publications and presentations. Minimum Requirement: Current PhD or Masters student involved in ongoing research at the intersection of machine learning and computer security. Strong computational background and programming skills, particularly with Python . Strong development skills using standard machine learning packages, such as scikit-learn, PyTorch, Tensorflow, and Keras. Experience with Linux and Jupyter notebooks . Desired Qualifications: Strong written and verbal communication skills . Ability to document and explain technical concepts clearly and concisely . * Ability to work as part of a remote team ; /At FireEye we are committed to our #OneTeam approach combining diversity, collaboration, and excellence. All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability./