Siemens Healthineers SHL (Sr.) Mathematics Modeling Research Scientist (Beijing)西门子医疗 (高级)数学模型研究员

Job description

What are my responsibilities?

Mission of Function : Conduct technical innovation in the rich soil of diverse needs from USA headquarter (corresponding to German/global customers' requirements including China's). Success on the job means the discovery and development of new technologies and applying them to significantly impact business and hence change customer’s works or lives.

Dimensions of Function : Conduct math research and development in the wide field of artificial intelligence, especially deep learning, machine learning, natural language processing, big data intelligent analytics, medical image and /or report processing / analysis and understanding. Continuously strengthen expertise in the technical domain. You will have the opportunity to test your knowledge in a challenging problem-solving environment. You will be encouraged to think out-of-the-box, innovate and find solutions to real-life problems.

Areas of Responsibilities/Tasks : 1. Research, design, and implement Mathematics Modeling in Natural Language Processing for Medical Image Visualization and Report Analysis problems. 2. Advance the state-of-the-art , including generating international-standard high-quality patents. 3. Work on large-scale, real-world math problems.4. Fast prototyping, feasibility studies, specification and implementation of image, reportand video analysis mathematics cores . 5. If necessary, work with customers to understand requirements and deliver solutions.

What do I need to qualify for this job?

Required Knowledge/Skill/Experience : * indicates terms especially for lead research scientist,
** indicates terms especially for (junior) research scientist, and *** indicates terms especially for senior research scientist.
1. Education:
• * Ph.D. in Applied Math, Statistics, orother math related subjuects.
• * >=5 years strong industry company background in math core of Deep Learning / Machine Learning, or equivalent working experience in university.
• ** Master degree plus >=2 years In-depth related math R&D experience in the past, in which at least 1 year has to berelated withdeep learning or NLP.
• *** Master degree (or higher) plus >=4 years In-depth related math R&D experience in the past, in which at least 3 year has to berelated withdeep learning or NLP.
• Graduate research and internship experience in Computer Vision, Machine Learning and Image and Language Understanding preferred.
2. Knowledge:
• Well versed and hands-on in math problem programming using Python, R, C++,(better alsohave experience withCaffe, Tensorflow, PyTorch), andknow aboutsoftware analysis, data structure and algorithm design and development.
• Model-wise,well understandor even have experiences in GPU Convolutional Neural Network (CNN), Reinforcement Deep Learning (RDL), and/orGenerative Adversarial Network (GAN) programming.
• For NLP problem, well understanding or even experiences with MXnet,NLP tools (like Word2Vec, GloVe, Seq2Seq), Recurrence Neural Network (RNN), and LSTM is a strong plus. .
• High ranking in math competition, or publication in good math journals or conferences can greatly add scores.
3. Experience in customer engagement, requirement study, project definition and acquisition is also a plus. This implies strong interpersonal, communication, and presentation skills.
4. Experience in healthcare and medical image and report applications is highly desirable.
5. Proven record in research, innovative thinking, real world problem solving and a hands-on, can-do mentality.
6. Good written and verbal communication skills in both Chinese and English.
7. Strong collaboration skills and ability to thrive in a fast-paced environment.

职位名称：数学模型研究员（Mathematical Modeling Research Scientist）

工作内容：

· 设计新型人工智能算法数学模型，用来解决医学影像和报告分析中遇到的问题；
· 攻关前沿数学问题
· 数学问题的咨询顾问

具备能力：

· 有超强的数学独立思考和研究能力；
· 在数学建模、统计，理论和应用层面都要有自己独到的见解;
· 有用Python, R, C++ 解决数学编程问题的经验;
· 对人工智能、深度学习/机器学习、计算机视觉/图形学、自然语言处理有一定的认识；
· 流利的中英文读写；
· 很强的团队协作精神，能在快节奏中出成绩。

加分项：

· 在数学领域相关会议和期刊发表过论文；
· 参加过数学建模或算法大赛，成绩优异；
· 最好有统计或应用数学，或其他相关数学领域的博士学位。如果是相关领域硕士，需要有2年以上数学科研经验，其中至少1年在深度学习或机器学习领域；
· 对模型加速的硬件和软件实现有独到的想法。