Jobs Posted on the Whova Community Board of The 18th International Conference on Data Mining (ICDM 2018)
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Faculty Positions in ECE at Mississippi State
Mississippi State University Faculty positions in all areas of electrical and computer engineering at all levels, including but not limited to, Cybersecurity, Cyber Physical Systems, Embedded Systems, etc.
... Link:https://www.ece.msstate.eduSee More >>
Researcher for Educational Data Mining
Beijing Normal University Conduct Data Analytics Research in Education Domain.
Grab Grab is looking for talented data scientists with expertise in Machine Learning, Computer vision, Text mining, Natural language processing, Mapping and Sensor fusion. As a data sc... ientist @ Grab you will have the unique opportunity to work on some of the most challenging and fascinating problems in transport, geo-spatial data mining, economics, and logistics, wrangle large scale data, build and deploy models that push our business metrics to their bounds and move Southeast Asia Forward. We foster a culture where we enjoy raising the bar constantly for ourselves and others, and that strongly supports the freedom to explore and innovate. Get to know the Role and day-to-day activities: • Build, validate, test, and deploy machine learning models (e.g. predictive, forecasting, clustering) using proven and experimental techniques. Deploy an online learning model where applicable; • Define hypotheses, develop and execute necessary tests, experiments, and analyses to prove or disprove them; • Translate data speak to human speak by effectively conceptualizing analysis to team members and business stakeholders; The must haves: • Ph.D. graduate, or Masters (with at least 3 years of experience), in Computer Science, electrical/electronics engineering, Statistics, or Optimization, • Deep understanding and hands-on experience in Deep Learning (CNN, RNN/LSTM), Reinforcement Learning, besides generative (HMMs) and discriminative models (CRF, Random Forest, Gradient Boosted Trees), dimensionality reduction and manifold • Hands-on experience using Keras, Tensorflow, Theano or Caffe, as well as Scikit Learn; • Proficient in programming languages like Python, Java, Scala or C++; Really nice to haves: i) Experience in building ML models at scale, using real-time big data pipelines on platforms such as Spark/MapReduce. ii) Research publications on NIPS, ICML, CVPR, KDD, AAAI, AISTATS, ICDM or other similar top AI and data mining conferences. Grab is Southeast Asia's leading Online to O
Link:https://grab.careers/job Grab is Southeast Asia's leading Online to Offline (O2O) mobile platform. We use data and technology to improve everything from transportation to payments across a region of more than 620 million people. Working with governments, drivers, passengers, and the community, we aim to unlock the true potential of the region by solving problems that hinder progress.
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Enterprise and Senior Data Scientists
PMI Within the Enterprise Analytics and Data Managements global function you can use your talents to tackle enterprise-wide challenges and help in shaping up our smoke-free future.... > We invent and implement algorithms, we design and build analytical pipelines – all with leveraging from domains like statistics, machine learning, information and graph theory, data mining, optimization, complex network analysis etc. We work in international teams with huge cultural diversity and we interact not only with other fellow data scientists, but also with data engineers, DevOps, business owners, data architects, security and privacy experts, etc. We mostly write our analytical code in Python, but we're not afraid of R, Java and even Scala. Last but not least, we are strong supporters of Open Source
Link:https://stackoverflow.com/jobs/companies/philip-morris-internationalSee More >>
Research Fellows, Research Scientists and Research Engineers
Living Analytics Research Centre LARC is a research centre located at Singapore Management University in partnership with Carneigie Mellon University . We work on various data science problems related to smart na... tion analytics. We have different job openings for Research Fellows , Research Scientists and Research Engineers from backgrounds like AI , ML , Deep Learning , Crowdsorcing, Urban Computing , HCI and Visualization. Drop by our booth at ICDM connect or contact us by email.
Link:https://larc.smu.edu.sgSee More >>
Postdoc in Data Mining and Machine Learning
CISPA Helmholtz Center for Information Security We are looking for excellent researchers with a PhD and strong background in Data Mining, Machine Learning, or Statistics. You are expected to do world class research, participate... in teaching, as well as supervision of MSc and PhD students.
We offer a contract of two years at the E14 100% level of the public employment scale of the German Federal Government, in an world leading dynamic research environment.
The Exploratory Data Analysis group is part of the newly founded CISPA Helmholtz Center for Information Security in Saarbrucken, Germany. It is part of the famous Saarland Informatics Campus, which in addition to CISPA, hosts the Saarland University, the Max Planck Institute for Informatics, the Max Planck Institute for Software Systems, and the German Research Center for Artificial Intelligence. The Helmholtz Association is the largest research organization in Germany, a factor three to four larger than Max Planck. CISPA is the first research center of the Helmholtz Association within the general field of computer science.
To apply, please contact Jilles Vreeken (jv@cispa.saarland) with a full scientific cv, letter of motivation, publication list, and contact details for two references.
Postdoc / Research scientist @ KAUST - multiple positions, all areas
KAUST Postdocs and Research scientists @ KAUST. Multiple positions available in all areas of CS. Required qualifications: PhD (or close to graduation) and good publication record.... r>KAUST offers excellent research environment, and very competitive salary/benefits package. For information, or to arrange 1-1 meeting at ICDM, please contact Prof. Panos Kalnis: panos.kalnis@kaust.edu.sa Link:
Http:/www.kaust.edu.saSee More >>
Faculty positions @ KAUST - all ranks, multiple openings
KAUST Faculty positions @ KAUST. Multiple positions available at all ranks. We are mainly interested in Computer Systems, Data Science, Machine Learning and Cybersecurity.
KAUST ... offers excellent research environment, and very competitive salary/benefits package.
Adobe The challenge
Adobe is looking for a Data Science PhD Intern who will be challenging problems in building the next generation of marketing cloud products by leveraging machine... learning, predictive modeling and optimization techniques.
What you’ll do
• Develop predictive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques.
• Solve challenging Data Science problems such as sparse data, online learning, reinforcement learning etc. when solving business problems in digital marketing.
• Develop and implement scalable and efficient modeling algorithms that can work with large-scale data in production systems
• Collaborate with product management and engineering groups to develop new products and features.
What you need to succeed
• PhD students enrolled in US university programs, such as Computer Science, Electrical Engineering, Statistics, Applied Math, Econometrics, Operations Research, or other related fields.
• Deep understanding of statistical modeling, machine learning, deep learning, or data mining concepts, and a track record of solving problems with these methods.
• Proficient in one or more programming languages such as Python, Java and C
• Familiar with one or more machine learning or statistical modeling tools such such as R, SciKitLearn, SparkML(MLlib), Tensorflow
• Strong analytical and quantitative problem solving ability.
• Excellent communication, relationship skills and a strong team player.
Preferred Qualifications • Research experience in reinforcement learning, active learning, recommendation system. • Experience with big data techniques (Hadoop, MapReduce, Spark) and querying tools (such as Hive, Pig, Impala).
• Experience with relational (SQL) and NoSQl Databases.
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Data Scientist (Full-time)
Adobe The challenge
Adobe is looking for a Data Scientist who will be building the next generation of marketing cloud products by leveraging machine learning, predictive modeling an... d optimization techniques. These products would help businesses understand, manage, and optimize the experience throughout the customer journey.
What you’ll do
• Develop predictive models on large-scale datasets to address various business problems through leveraging advanced statistical modeling, machine learning, data mining or deep learning techniques.
• Develop and implement scalable and efficient modeling algorithms that can work with large-scale data in production systems
• Research and implement algorithms to optimize customer marketing journey using approaches such as reinforcement learning, HMM and/or deep learning
• Gain insight into marketing content using NLP and/or deep learning approaches
• Research and develop state-of-the-art ML solutions to address the challenges in Data Science such as cold start, sparse and noisy data etc.
What you need to succeed
• PhD in Computer Science, Operations Research, Statistics, Electrical Engineering, Applied Math, Econometrics, or other related fields.
• Deep understanding of statistical modeling, machine learning, deep learning or data mining concepts, and a track record of solving problems with these methods.
• Proficient in one or more programming languages such as Python, Scala, Java and C.
• Familiar with one or more machine learning or statistical modeling tools such such as R, SciKitLearn, SparkML(MLlib), Tensorflow.
• Strong analytical and quantitative problem solving ability.
Preferred Qualifications
• Knowledge of deep learning, reinforcement learning, experimental design, ANOVA, statistical inference, and multivariate testing.
• Track record of publications in the fields of Statistics, Operation Research, or Reinforcement Learning
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TU Dortmund University Germany and France aim at a collaboration in machine learning research. In this context, the Competence Centre for Machine Learning Rhine-Ruhr (ML2R), funded by the Federal Minist... ry of Education and Research (BMBF), is now being launched in Dortmund and Bonn/Sankt Augustin. The TU Dortmund University, the University of Bonn and the Fraunhofer Institutes for Intelligent Analysis and Information Systems IAIS in Sankt Augustin and for Material Flow and Logistics IML in Dortmund will jointly investigate models of machine learning for their understandability, fairness, traceability and robustness and develop new model classes. Distributed learning, learning from data streams, embeddings, knowledge graphs, modern hardware for machine learning, Bayes' approaches to deep learning and interactive data exploration are some of the topics, according to the motto "a good theory is the best practice". Dortmund has a history of excellent research in machine learning at the Chair of Artificial Intelligence, Prof. Dr. Katharina Morik. The close connection between theory and practice is a leitmotif that was made clear by the first efficient implementation of the support vector machine, SVM_light, by her doctoral student Thorsten Joachims. Similarly, the successful spin-off RapidMiner illustrates that basic research also facilitates practical developments and applications.
We offer doctoral positions in all key aspects, provided that you have outstanding academic performance, a degree in computer science and previous knowledge of machine learning, e.g. by attending relevant courses during your studies or by publications at the respective conferences. More information can be found on the web-site. Please send digital applications with the usual documents stating ML2R in the subject to: office@ls8.cs.tu-dortmund.de Link:http://www-ai.cs.uni-dortmund.de/ML2R/ml2r_jobs.htmlSee More >>
Assistant Prof in Business Analytics / Data Mining / Machine Learning
Deakin University, Dept of Info Sys and Business Analytics Join a group of academics interested in exploring business applications of data mining and machine learning in the Department, which is home to IBM Centre of Excellence in Busines... s Analytics, and a new Advanced Business Analytics Lab. The position will involve both research and teaching, in a well balanced mix. We have formal partnerships with IBM, SAS and Microsoft, and are involved in projects with industry and with other academics across Deakin Business School, in Marketing, Accounting, Finance, Management and Info Sys. We teach mainly business students and offer Master of Business Analytics and Bachelor of Business Analytics, also degrees in Information Systems, and PhD programs. We are involved in training and running workshops for the industry and the government. You need to have completed a PhD in Data Science / Data Analytics / Machine Learning (or similar). publications in high quality journals will be expected. If interested, talk to Prof Jacob Cybulski at the conference, or get in touch with our Head of Department, Prof Rens Scheepers or Director of Teaching Prof Dilal Saundage. Applications close 6 Jan 2019.
Link:https://jobs.deakin.edu.au/psc/HCMP/EMPLOYEE/HRMS/s/WEBLIB_DU_JOATT.ISCRIPT1.FieldFormula.IScript_OpenAttachment?filename=20181107102123_180817_-_Assistant_Professor.pdf&fileusername=180817_-_Assistant_Professor.pdfSee More >>
Ph.D. Position for Computer Architecture and Optimization for Machine Learning Applications
TU Dortmund University Informatik 12, at the Department of Computer Science at TU Dortmund University, is responsible for the entire education and most of research for embedded systems and computer engi... neering. The Design Automation of Embedded Systems Group in Informatik 12 (Prof. Dr. Jian-Jia Chen) offers a job position for Ph.D. (Wissenschaftlichen Mitarbeiter) Positions in the areas of "Computer Architecture and Optimization for Machine Learning Applications" by salary grade TV-L E 13. The possibility to pursue a PhD degree exists. The vacancy shall be filled in 2018 or early 2019.
The applicants should hold a master/diploma degree in the areas of Computer Science, Informatics, or Electrical Engineering (with a focus on Computer Engineering).
The working language is English. Beneficial is basic expertise in one or more of the following areas: "Embedded Systems“, "Real-Time Systems", "Computer Architecture", and “Real-Time Operating Systems“.
TU Dortmund University strives at raising the quota of women in research and will therefore especially welcome female candidates. Disabled persons with equivalent expertise will be preferred. Candidates with excellent grades can send their full application including covering letter, CV, research statement, and certificates until the job opening is filled via email to Prof. Dr. Jian-Jia Chen. There is no specific application deadline, but the application documents will be processed as soon as possible.
Fraunhofer IAIS Data Science and Machine Learning are your major interest? At Fraunhofer, we are now offering an exciting job in the areas of Data Science and Machine Learning.
Fraunhof... er is the biggest organization for applied sciences in Europe. In 2017, it was ranked as one of the top three "Most Attractive Employers by Natural Sciences Students“.
In the Fraunhofer-Institute IAIS, more than 250 employees develop customized solutions for the integration and analysis of data for our customers in the industry. The emphasis lays on competencies in the areas of Big Data, Multimedia Content Analytics, Information Integration and Enterprise Modeling and Enterprise Analysis.
In the Business Area Intelligent Media and Machine Learning of the IAIS within the department Media Engineering, you will be working on conceptualizing and implementing innovative, data driven applications. With us, you can apply your growing scientific and practical knowledge of Data Science and Machine Learning in projects for customers from the industry.
Your tasks:
* Conceptualizing and developing modern Machine Learning methods * Publications in prestigious Machine Learning journals and on conferences, e. g. JMLR, ICML, NIPS, CVPR, ICDM, DSAA and ICLR * Participation in the implementation of learning solutions in customer projects for image, text- or time series analysis
