Information Systems and Data Science

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تو این تاپیک میخوایم به معرفی این رشته ها و دانشگاه هایی که اینها رو ارائه میدن بپردازیم. دوستان هرکدوم اگه اطلاعاتی دارن اینجا به اشتراک بذارن تا هممون استفاده کنیم.

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این رشته ها در دانشگاه های مختلف در دپارتمان های مختلفی ارائه میشن. بعضی از آنها در بیزنس اسکول ها بعضی در دپارتمان های کامپیوتر ساینس و حتی در دپارتمان مهندسی صنایع هم این رشته ها وجود داره و این نشان دهنده اینه که این رشته ها حد و مرز مشخصی ندارند و میتونند درگیر فیلد های متفاوتی بشن. حتی در دپارتمان های زیستی در قالب Bioinformatic یا حتی Neuroinformatic و Medical Informatic.

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20 دانشگاه برتر جهان طبق رنکینگ QS در زمینه Computer Science & Information Systems در سال 2015.

1 - MIT
2- Stanford University
3- University of Oxford
4- Carnegie Mellon
5- Harvard University
6- University of California,Berkeley
7- University of Cambridge
8- The Hong Kong University of Science & Tech
9- ETH Zurich
10- Princeton University
11- National Uni of Singapore
12- The University of Hong Kong
13- The University of Melbounre
14- University of Edinburgh
15- Imperial College London
16- Uni of Toronto
17- University of California , Los Angles
18- The Chinese university of Hong Kong
19- The University of Tokyo
20- The University of Washington

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رتبه بندی Information Systems بیزنس اسکول های آمریکا و میانگین نمرات GMAT منبع: USNEWS

1 - MIT - 713
2- Carnegie Mellon - 687
3- University of Arizona - 646
4- University of Minnesota - Twin Cities - 683
5- University of Texas - Austin 690
6- University of Maryland College Park - 662
7- New york University - 721
8- University of Pennsylvania - 728
9- Georgia State University - N/A
10- Stanford University - 732
11- Indiana University - Bloomington - 668
12- Arizona State University - 673
13- University of Michigan - Ann Arbor - 702
14- Georgia Tech - 676
15- University of California - Berkeley - 717
16- Temple University - 641
17- University of Texas - Dallas - 673

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برنامه های دانشکده انفورماتیک University of Iowa

• Bioinformatics and Computational Biology
• Geoinformatics
• Health Informatics
• Information Science
• http://informatics.grad.uiowa.edu
• همینطور که تو خود وبسایت دانشکده نوشته یک برنامه ی بین رشته ای هستش که از رشته های مختلف میتونن با توجه به سابقه تحصیلی و علاقه مندی پژوهشی شون روی یک فیلد انتخابی متمرکز بشن.

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The Research Project “Engaging Big Data” aims to turn streams of geographic and activity data into predictive models of activity and travel behavior, in order to test the viability of policy and infrastructure decisions before they are implemented, and guide and inform the urban and transport planning process. The goal is to dramatically improve the turnaround time, and lower the barrier-to-entry for implementing the latest agent-based, activity-oriented approaches to transportation modelling, applied to the open-source agent-based modeling framework, MATSim. Importantly, the methods developed should be applicable in both developing and developed urban contexts. A further goal will be to improve the means of protecting the privacy of people generating the data that drive these models, through machine learning and automated data synthesis. You will help develop a fully data-driven agent-based transportation model of Singapore, synthesizing multiple data streams, e.g. cellular, public transport, toll gantry and credit card transaction data into a coherent whole; and enriching these data with activity purpose using survey information. Concurrently, you will apply machine learning techniques to mine data sources and automatically synthesize model input data. Enrolled as an ETH PhD student you will take advantage of rich further learning opportunities such as participating in graduate courses, academic seminars and attending research conferences, academic exchange at ETH Zurich or other institutions and potentially also co-supervise students who write their MSc thesis at FCL.
You are interested in simulation modeling, machine learning, data analysis and applying these techniques in the field of transportation planning. You have proven experience in object-oriented programming in a major language, e.g. C++, C#, Java or Python, as well as analysing data and applying machine-learning approaches in R, SPSS and/or MatLab. You have a Masters degree in Computer Science, Engineering or Applied Mathematics. You are keen to work in an interdisciplinary team at one of the leading urban science research institutions. We offer a 3.5-year, fully funded PhD position in an inspiring environment at the Future Cities Laboratory of the Singapore ETH Centre with a competitive salary. As an interdisciplinary and international team we will nurture a collaborative spirit and strive for disciplinary excellence. Travel to conferences and academic training will be as much part of the package as free choice of hardware and a well-equipped workplace with access to facilities such as a gym and great food options in the vicinity. The PhD will be granted by ETH Zurich, one of the World’s top 10 universities, and co-supervised by Prof. Dr. Kay Axhausen as well as an external supervisor.
For further information please contact Mr. Pieter J. Fourie by e-mail fourie@ivt.baug.ethz.ch (no applications) and visit our website http://www.fcl.ethz.ch/module/engaging-mobility/.

Applications with motivation letter, CV, diplomas and a portfolio of previous relevant projects should be sent online via the blue button "Apply now" below with attention to: ETH Zurich, Mrs. Corina Niescher, Human Resources, CH-8093 Zürich. Applicants should be prepared to be tested on their programming and analysis abilities in a short 'data challenge'. The application deadline is on 30th Nov 2015 and applications will be reviewed as they come in.

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PhD student in data visualization of text

Occupation : Full-time
Period : Fixed-term contract
Place : Leuven
Apply no later than : November 30, 2015

Patient records and clinical reports include a vast amount of crucial information that is stored as free text, but that is unstructured and requires a human to make sense of it (e.g. vague pain in belly which radiates to back). Research into semantic processing of these texts (machine reading) is a hot topic at the moment and aims to not merely extract the individual components of these texts, but actually come to a deeper machine understanding, including temporal, spatial and causal structures and relationships.
PhD student in data visualization of text

The Visual Data Analysis Lab at KU Leuven (vda-lab.be) is a young group of researchers focusing on visual design, interaction design and scalability to help make sense in the world of big data. The group resides in the Bioinformatics research group at the university and is part of ESAT-STADIUS. It acts under the umbrella of the Data Visualization Lab together with groups from computer science and architecture. Patient records and clinical reports include a vast amount of crucial information that is stored as free text, but that is unstructured and requires a human to make sense of it (e.g. "vague pain in belly which radiates to back"). Research into semantic processing of these texts (machine reading) is a hot topic at the moment and aims to not merely extract the individual components of these texts, but actually come to a deeper machine understanding, including temporal, spatial and causal structures and relationships.
Website unit

Project

The ACCUMULATE consortium recently received 4-year funding for Acquiring Crucial Medical Information Using Language Technology. Our role in this project is to develop data visualization methods to (a) support the development of the machine reading algorithms, and (b) present the extracted information to the doctor. For the first, we will for example create abstract interactive visualizations showing the effects of using different parameters in the algorithms; the latter will include (but not be limited to) creating visuals that combine the information from the unstructured text with additional information such as episodes, medication, etc.


Profile

The ideal candidate has a strong MSc degree in computer science or design, or a field related to human-computer interaction. He or she has an eye for visual design or experience in data visualization (e.g. using D3 or Processing), preferably of text. The candidate also has good programming skills (preferably javascript).

Offer

We offer a fully-funded PhD research position for 4 years. In this position, you will be able to work with the users, develop visual designs, and implement and evaluate data visualizations.

Interested?

To apply, please send an email to jan.aerts@kuleuven.be, and include (preferably in PDF): [a] your CV, [b] two references (with email and phone number), [c] one or more figures and/or screencasts of previous data visualization work, if you have any.
We will start reviewing applications in October 2015, but applications will be considered until the positions are filled. Starting date is as soon as possible after January 1st, 2016.

You can apply for this job no later than November 30, 2015 via the
online application tool

https://icts.kuleuven.be/apps/jobsit...tures/53474163

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PhD candidate at the Department of Computer and Information Science, within “Querying Big Data”

The Faculty of Information Technology, Mathematics and Electrical Engineering (http://www.ntnu.edu/ime) at the Norwegian University of Science and Technology (NTNU) has a vacancy for one PhD candidate position at the Department of Computer and Information Science (http://www.ntnu.edu/idi).Information about the department
The Department of Computer and Information Science is the largest department in the Faculty of Information Technology, Mathematics and Electrical Engineering, with approx. 140 employees of which the scientific personnel are organized in 6 research groups. The PhD candidate will be affiliated with the Data and Information Management Group (http://www.ntnu.edu/idi/groups/dif). Further information can be found at the department’s and the group’s web pages. Work description
The PhD candidate will be a member of the ExiBiDa project team (https://www.ntnu.edu/idi/exibida/).In ExiBiDa, we will focus on exploratory analysis and querying contents in Big Data, and develop frameworks and scalable techniques for supporting such analytical queries. In particular, the PhD candidate will work with challenges related to efficient algorithms and index structures for processing Big Data.The appointment is for a term of 4 years, with duties equivalent to 25 %, or 3 years without duties. Duty work, if relevant for a candidate, will primarily be related to support of education tasks. This is a researcher training position aimed at providing promising future researchers the opportunity of academic development in the form of a doctoral degree. Qualifications

A master's degree in Computer and Information Science or equivalent with very good results is required, with an average grade B or better as measured in ECTS (European Credit Transfer System) grades, or an education at the equivalent level. A solid knowledge of database systems or algorithms is essential, and a research-oriented master thesis within one of these areas is expected. Good programming skills are required. Applicants who do not master a Scandinavian language must provide evidence of good English language skills, written and spoken. The following tests can be used as such documentation: TOEFL, IELTS or Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:

• TOEFL: 600 (paper-based test), 92 (Internet-based test),
• IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test accepted),
• CAE/CPE: grade B or A.

In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases the candidate’s language skills will be assessed in a personal interview. Formal regulationAppointments are made in accordance with the regulations in force regarding terms of employment for PhD candidates issued by the Ministry of Education and Research, with relevant parts of the additional guidelines for appointment as a PhD candidate at NTNU. Applicants must undertake to participate in an organized PhD programme of study during their period of employment. The person who is appointed must comply with the conditions that apply at any time to employees in the public sector. In addition, a contract will be signed regarding the period of employment, including duty work if relevant. Applicants must be qualified for admission as PhD students at NTNU. Seehttp://www.ntnu.edu/ime/research for information about PhD studies at IME, NTNU. Salary conditionsThe position is in code 1017 Stipendiat, salary grade range 50-62 in the Norwegian State salary scale, and normally in salary grade 50-57, gross NOK 430 200 – 483 400 per year, depending on qualifications. A deduction of 2 % is made as a statutory contribution to the Norwegian Public Service Pension Fund. GeneralWe can offer

• a professional research environment targeting scientific and technological challenges with dedicated colleagues
• attractive schemes for housing loan, insurance and pension in the Norwegian Public Service Pension Fund

The Faculty of Information Technology, Mathematics and Electrical Engineering wants to attract outstanding and creative candidates who can contribute to our ongoing research activities. We believe that diversity is important to achieve a good, inclusive working environment. We encourage all qualified candidates to apply, regardless of the gender, disability or cultural background. For further information about the position, please contact Professor Kjetil Nørvåg, Email:noervaag@idi.ntnu.no.For information about processing of applications, please contact Senior Executive Officer Anne Kristin Bratseth, Phone +47 73 59 67 15, Email: anne.kristin.bratseth@ime.ntnu.noThe appointment is subject to the conditions in effect at any time for employees in the public sector.Under Section 25 of the Freedom of Information Act, information about the applicant may be made public even if the applicant has requested not to have his or her name entered on the list of applicants. The application must contain

• Curriculum vitae (CV) with information about the candidate’s prior training, exams, and work experience
• certified copies of transcripts and diplomas
• a Statement of Purpose (including a short presentation of the motivation for a PhD study and how the applicant sees his/her background suitable, and the applicant’s view of research challenges within the area of the PhD position and how the competence of the applicant can contribute to solving these challenges) (2 pages)
• at least 2 reference persons
• a copy of the master thesis (in PDF), or, for those who are near to completion of their MSc, an extended abstract combined with a statement of how and when the applicant plans to complete the thesis (1 page)

Incomplete applications will not be taken into consideration.

The application must be sent electronically as one combined PDF file via this page. Mark the application: IME 068-2015Deadline for applications: 2015-12-09

http://www.jobbnorge.no/en/available...rying-big-data

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PhD student in Computer Science (SAPPAO-project)

The Faculty of Science, the Leiden Institute of Advanced Computer Science (LIACS), vacancy 15-372The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) is looking for:1 PhD student in Computer Science (SAPPAO-project) (1.0 fte)
Vacancy number: 15-372

Key responsibilities

In the SAPPAO project 1 positions are available for ambitious PhD students. The SAPPAO-project aims to optimise the accuracy and reliability of predicting scheduled flight times by analysing historical flight data and data on the associated disruptive events on the flight network. The potential impact of this ambitious project is enormous: saving millions of euro’s on better utilisation of airplanes, decreased fuel consumption, decreased CO2-emissions, decrease of ambient noise, and better use of time for passengers and airports.The PhD student will work on data mining and optimization algorithms, making them applicable to this task.The project is a collaboration between LIACS (Leiden), IIT Rourkee (India), and GE Aviation (India).

Selection criteria

Successful PhD candidates will have:
• A master in data science, computer science or artificial intelligence;
• A strong background in a strong background in data mining/machine learning/evolutionary computation.

Research at our faculty/ Institute

LIACS is the computer science institute of Leiden University, engaged in both research and education in the area of computer science, including bioinformatics and innovation management. The research at LIACS is broadly oriented. There are two research programs, both responsible for exploring the next frontier of ideas and techniques in their area such as research in the emerging area of bioinformatics. Close cooperation with industrial and academic research institutes, nationally and internationally, is the rule, not the exception.The Faculty of Science teaches more than 2,600 students in the context of 8 bachelor’s and 11 master’s programmes. Working at the Faculty of Science means being part of an exciting, dynamic scientific environment which sets high standards for its students, staff and support staff alike. The Faculty is known for its friendly and team-spirited atmosphere, which promotes mutual exchange of knowledge. For more information, seehttp://www.science.leidenuniv.nl.

Terms and conditions

We offer a full-time, 4 year term position, with a go/no go decision on the end of year 1. Salary range from € 2.125 to € 2.717 gross per month (PhD pay scale, in accordance with the Collective Labour Agreement for Dutch Universities).Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses(8.3 %), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside the Netherlands may be eligible for a substantial tax break.All our PhD students are embedded in the Leiden University Graduate School of Sciencewww.graduateschools.leidenuniv.nl. Our graduate school offers several PhD training courses at three levels: professional courses, skills training and personal effectiveness. In addition, advanced courses to deepen scientific knowledge are offered by the research school.We aim to employ more women in areas where they are underrepresented. Women are therefore especially invited to apply.

Information

Enquiries can be made to Professor Thomas Bäck , t.h.w.baeck@liacs.leidenuniv.nl. If you have any questions about the procedure, please contact our secretary Marloes van der Nat (e-mail: m.van.der.nat@liacs.leidenuniv.nl, telephone: +31-(0)71-5277061.Information about the faculty of science can be found athttp://www.science.leidenuniv.nl/index.php/english/ and about Leiden University athttp://workingat.leiden.edu/.

Applications

To apply for this vacancy, please send an e-mail to our secretary Marloes van der Nat (e-mail: m.van.der.nat@liacs.leidenuniv.nl. Please ensure that you upload the following additional documents quoting the vacancy number (15-372):
• A resume;
• A motivation letter;
• Your bachelor and master theses;
• Any publications and other material which may help us to assess your qualifications.Only applications received before December 1st, 2015 can be considered.
http://werkenbij.leidenuniv.nl/vacat...o-project.html

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2 PhD students in Computer Science (DAMIOSO project)

The Faculty of Science, the Leiden Institute of Advanced Computer Science (LIACS), vacancy 15-371
The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) is looking for:
2 PhD students in Computer Science (DAMIOSO project) (1.0 fte)
Vacancy number: 15-371
Key responsibilities

In the DAMIOSO project 2 positions are available for ambitious PhD students. The DAMIOSO project aims at applying data mining, response surface modeling, and nonlinear optimization in the context of data intense simulations in computational fluid dynamics. Such simulations typically generate enormous amounts of data, often in the form of images.
Mining this data for relevant vs. irrelevant features and understanding the complex mapping between design geometry and such features are important research topics. Additional ambitious goals include learning a fast approximation of such a mapping through response surface modeling algorithms and using the learned approximation for optimization. Data handling of the corresponding vast amount of data, e.g., using an in-memory database, is also part of the project.
The project is a cooperation between LIACS (Leiden), CWI (Amsterdam), and the Honda Research Institute (Offenbach, Germany).
Selection criteria

Successful PhD candidates will have:
• A master in data science, computer science or artificial intelligence;
• A strong background in data mining/machine learning/evolutionary computation/data management and/or a strong background in computer graphics and feature analysis in images and videos;
• Interest in engineering applications and in the corresponding simulations, as the candidates will be working with commercial CFD simulation software.
Research at our faculty/ Institute

LIACS is the computer science institute of Leiden University, engaged in both research and education in the area of computer science, including bioinformatics and innovation management. The research at LIACS is broadly oriented. There are two research programs, both responsible for exploring the next frontier of ideas and techniques in their area such as research in the emerging area of bioinformatics. Close cooperation with industrial and academic research institutes, nationally and internationally, is the rule, not the exception.
The Faculty of Science teaches more than 2,600 students in the context of 8 bachelor’s and 11 master’s programmes. Working at the Faculty of Science means being part of an exciting, dynamic scientific environment which sets high standards for its students, staff and support staff alike. The Faculty is known for its friendly and team-spirited atmosphere, which promotes mutual exchange of knowledge. For more information, seehttp://www.science.leidenuniv.nl.
Terms and conditions

We offer a full-time, 4 year term position, with a go/no go decision on the end of year 1. Salary range from € 2.125 to € 2.717 gross per month (PhD pay scale, in accordance with the Collective Labour Agreement for Dutch Universities).
Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses(8.3 %), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. Candidates from outside the Netherlands may be eligible for a substantial tax break.
All our PhD students are embedded in the Leiden University Graduate School of Sciencewww.graduateschools.leidenuniv.nl. Our graduate school offers several PhD training courses at three levels: professional courses, skills training and personal effectiveness. In addition, advanced courses to deepen scientific knowledge are offered by the research school.
We aim to employ more women in areas where they are underrepresented. Women are therefore especially invited to apply.
Information

Enquiries can be made to Professor Thomas Bäck , t.h.w.baeck@liacs.leidenuniv.nl. If you have any questions about the procedure, please contact our secretary Marloes van der Nat (e-mail: m.van.der.nat@liacs.leidenuniv.nl, telephone: +31-(0)71-5277061.
Information about the faculty of science can be found athttp://www.science.leidenuniv.nl/index.php/english/ and about Leiden University athttp://workingat.leiden.edu/.
Applications

To apply for this vacancy, please send an email to our secretary Marloes van der Nat (e-mail: m.van.der.nat@liacs.leidenuniv.nl. Please ensure that you upload the following additional documents quoting the vacancy number (15-371):
• A resume;
• A motivation letter;
• Your bachelor and master theses;
• Any publications and other material which may help us to assess your qualifications.
Only applications received before December 1st, 2015 can be considered.
http://werkenbij.leidenuniv.nl/vacatures/phd-posities/15-371-vacature-universiteit-leiden-2-phd-students-in-computer-science-damioso-project.html