https://apply.refline.ch/845721/6221/pub/1/index.html

✔ @ApplyTime

#ApplyTime #Apply #Chance #QA #QA16

❓ ببخشید من به تازگی بعد از اندیشیدن‌های طولانی، تصمیمم رو نهایی کردم و می‌خوام کارای اپلای رو شروع کنم. کلاس زبان رو هم استارت زدم و هر جوری هست می‌خوام برم. از اونجایی‌که با هزینه‌ی شخصی نمی‌تونم اقدام کنم، حتما بدنبال فاند هستم. من رزومه‌م رو براتون بفرستم، به من می‌گین که آیا موفق می‌شم یا نه؟

🔍 اگر بعد از دیدن رزومه‌ی‌تان به شما بگوییم که موفق نمی‌شوید، بعد از آن‌همه اندیشیدن‌های طولانی، و مصمم شدن برای ساختن مسیری تازه، منصرف می‌شوید؟

❓ خب ... معلومه ... نه!!!

🔍 خب... پس بدون توجه به حرف‌های ما یا دیگران، برای دست‌یابی به هدف‌تان تلاش کنید.
رزومه‌ی هر کسی ممکن است نقطه ضعف‌هایی داشته باشد، جهت شناسایی نقاط ضعف رزومه، و دریافت مشاوره‌هایی در جهت بهبود آن‌ها می‌توانید آن‌را برای ما ارسال نمایید.

🌈 با ما در ارتباط باشید:

🎭 Admin: @Dr_Apply

✔️ @ApplyTime

😐

⚠️ Please be careful!

✔️ @ApplyTime

Workshop on Domain Adaptation for Visual Understanding (DAVU)
Joint IJCAI/ECAI/AAMAS/ICML 2018 Workshop

https://cmt3.research.microsoft.com/DAVU2018/

http://iab-rubric.org/ijcai-davu.html

Final Paper Submission Deadline: May 14, 2018
Note: Extended version of accepted papers will be invited for consideration in one of the prestigious journals (approval pending).

Visual understanding is a fundamental cognitive ability in humans which is essential for identifying objects/people and interacting in social space. This cognitive skill makes interaction with the environment extremely effortless and provides an evolutionary advantage to humans as a species. In our daily routines, we, humans, not only learn and apply knowledge for visual recognition,we also have intrinsic abilities of transferring knowledge between related visual tasks, i.e., if the new visual task is closely related to the previous learning, we can quickly transfer this knowledge to perform the new visual task. In developing machine learning based automatedvisual recognition algorithms, it is desired to utilize these capabilities to make the algorithms adaptable. Generally traditional algorithms, given some prior knowledge in a related visual recognition task, do not adapt to a new task and have to learn the new task from the beginning. These algorithms do not consider that the two visual tasks may be related and the knowledge gained in one may be used to learn the new task efficiently in lesser time. Domain adaptation for visual understanding is the area of research, which attempts to mimic this human behavior by transferring the knowledge learned in one or more source domains and use it for learning the related visual processing task in target domain. Recent advances in domain adaptation, particularly in co-training, transfer learning, and online learning have benefited the computer vision significantly. For example, learning from high-resolution source domain images and transferring the knowledge to learning low-resolution target domain information has helped in building improved cross-resolution face recognition algorithms. This special issue will focus on the recent advances on domain adaptation for visual recognition. The organizers invite researchers to participate and submit their research papers in the Domain Adaptation workshop. Topics of interest include but are not limited to:
Novel algorithms for visual recognition using
Co-training
Transfer learning
Online (incremental/decremental) learning
Covariate shift
Heterogeneous domain adaptation
Dataset bias

Domain adaptation in visual representation learning using
Deep learning
Shared representation learning
Online (incremental/decremental) learning
Multimodal learning
Evolutionary computation-based domain adaptation algorithms

Applications in computer vision such as
Object recognition
Biometrics
Hyper-spectral
Surveillance
Road transportation
Autonomous driving
Submission Format: The authors should follow IJCAI paper preparation instructions, including page length (e.g. 6 pages + 1 extra page for reference).

Important Dates:
Submission deadline: May 14, 2018
Decision notification: May 25, 2018

Paper Submission Page: https://cmt3.research.microsoft.com/DAVU2018/

—
Mayank Vatsa, PhD
Vice President (Publications), IEEE Biometrics Council
Head, Infosys Center for Artificial Intelligence
Associate Professor, IIIT-Delhi, India
Adjunct Associate Professor, West Virginia University, USA
http://iab-rubric.org/
http://cai.iiitd.ac.in/
http://ieee-biometrics.org/


✔️ @ApplyTime

#ApplyTime #English #Apply #QA #QA9

سلام
❓من خیلی عجله دارم برای ادامه‌ی‌ تحصیل در خارج از کشور‌؛ و نیاز به مدرک زبان دارم. ولی زبانم خوب نیست. می‌شه یه روشی پیشنهاد کنین که خیلی خیلی زود بتونم جواب بگیرم؟

💡 متاسفانه هیچ روش خیلی خیلی سریعی برای یادگیری زبان وجود ندارد. فرآیند زبان‌آموزی در دنیای واقعی و به‌دور از تبلیغات، فرآیندی زمان‌بر بوده که در بستر زمان رخ می‌دهد. برای آن‌که این فرآیند تسریع شود لازم است که زمان و انرژی زیادی بگذارید و با تلاش زیاد و مستمر دائما خود را با زبان درگیر کنید. شرکت در کلاس‌های زبان، تمرین کردن با خودتان یا با دوستی که در حال زبان‌آموزی است یا زبانش از شما بهتر می‌باشد، و البته داشتن معلوم خصوصی می‌تواند به سرعت بخشیدن این روند کمک کند.

✔️ @ApplyTime

❓آخه من شنیدم که می‌گن آزمون تافل یا آیلتس تکنیکیه و اگه اون تکنیک‌ها رو بلد باشی می‌تونی به نمره‌ی مطلوب برسی. برخیا میگن طی 10-20 جلسه هم ممکنه. نظر شما در این‌باره چیه؟

💡 نظر ما این است که فرآیند زبان‌آموزی، فرآیندی زمان‌بر بوده و تنها در بستر زمان رخ می‌دهد!! در آزمون‌های استاندارد زبان مانند تافل یا آیلتس، با وجود این‌که دانستن برخی از تکنیک‌ها می‌تواند به شما کمک کند که زمان، انرژی و فکرتان را در هنگام آزمون بهتر مدیریت کنید، اما موفقیت در این آزمون‌ها ریشه در دانش زبان عمومی شما دارد که کسب این مهارت در زبان، تنها در بستر زمان رخ می‌دهد.

🔍 چنان‌چه قصد اپلای دارید و زبان شما مناسب نمی‌باشد، برای این‌که به هدف خود یعنی تحصیل در یک کشور خارجی برسید، حتما زمانی را هم برای زبان‌آموزی کنار بگذارید؛ نسبت به سطح زبان خود و دریافت نتیجه‌ی مطلوب واقع‌بین بوده و با خودتان صادق باشید!

✔️ @ApplyTime

❓می‌تونم یه کشوری برم اول زبان بخونم و بعد همون‌جا یا یه کشور دیگه ادامه‌ی تحصیل بدم؟

💡 بله این امکان وجود دارد که ابتدا برای دوره‌ی زبان ِ برخی از کشورها اقدام کنید و پس از کسب مدرک زبان مطلوب در همان‌جا یا کشور دیگری به تحصیل در رشته‌ی خودتان بپردازید.

🎈 اما ما این روش را اصلا توصیه نمی‌کنیم. چرا که طی کردن دوره‌ی زبان در یک کشور خارجی بسیار پر هزینه می‌باشد. مثلا ممکن است شما در ایران با 1 یا 2 میلیون تومان و صرف مدت زمان کافی (بسته به سطح کنونی‌تان) به نتیجه‌ی مطلوب برسید. اما رسیدن به این نتیجه‌ی مطلوب در یک کشور خارجی چند ده میلیون تومان برای شما هزینه خواهد داشت؛ و از نظر زمانی نیز آن‌طور نیست که خیلی زیاد سرعت رسیدن به پاسخ را افزایش دهد.

🔍 چیزی که برای ادامه‌ی تحصیل در یک دانشگاه خارجی نیاز دارید (از منظر زبان)، صرفا یک مدرک زبان در سطح مطلوب است؛ این‌که این مدرک زبان را در ایران و یا یک کشور خارجی کسب کرده باشید، در رزومه‌ی شما تاثیری نخواهد داشت.

✔️ @ApplyTime

❓یعنی من اول برم چند ماه فقط زبان بخونم بعد تازه به فکر کارای اپلای باشم؟

💡 با وجود این‌که این روش بسته به شرایط دانشجو می‌تواند استراتژی خوبی باشد، اما پیشنهاد ما این است که این امور را به صورت موازی جلو ببرید. یعنی هم‌زمان که در حال زبان‌آموزی هستید، مقدمات اولیه برای اپلای را نیز آماده کنید.

🔍 مقدمات اولیه‌ی اپلای نظیر پیدا کردن کشوری مناسب با اهداف شما، دانشگاهی که رشته‌ی شما را داشته باشد و با شرایط شما سازگار باشد، پیدا کردن استاد مناسب و یا بورسیه‌های تحصیلی، و البته آماده‌سازی داکیومنت‌هایی نظیر رزومه، انگیزه‌نامه، کاور لتر، و متن ایمیل به استاد (که داکیومنت‌های بسیار مهمی هستند) نیازمند صرف زمان زیادی می‌باشند.

🎾 بنابراین پیشنهاد ما موازی‌کاری با یک استراتژی مطلوب می‌باشد.

🔰 در مسیر اپلای، از آغاز تا پرواز با شما هستیم. با ما در ارتباط باشید:

🎭 Admin: @Dr_Apply

✔️ @ApplyTime

The Knowledge Engineering Group of the Department of Computer Science at the
Technical University in Darmstadt, Germany
has an immediate opening for a

*Doctoral Researcher* (Wissenschaftlicher Mitarbeiter)

in the area of

*machine learning*.

The task of the job holder is primarily to carry out the project work for a
research project for the *early detection of epidemiological hazards* using
machine learning.

*Deadline* for application: *20th of May 2018*

https://www.ke.tu-darmstadt.de/staff/jobs/ESEG

✔️ @ApplyTime

Bayesian models for forecasting in the supply chain

*BRIEF SUMMARY*

The global economy relies heavily on the consumption of goods of all kinds: food, textiles, electronics, equipment, vehicles, etc. The supply chain is the mechanism that accounts for the physical flows of these consumed goods. The supply chain consists of logistics (warehouses, transport vehicles, packaging), finance (billing and payment), and IT (stock status, manufacturing, ordering and shipping). Its efficient functioning has a direct impact on the performance of the economy, on the environment (transport, storage, destruction of useless stock) and on the working conditions of the employees. In this thesis, the objective is to predict the evolution of the outputs in the supply chain, i.e. quantities in locations of storage or sales. The research work of this thesis can be divided into two parts: (1) mathematical modeling of the supply chain, and (2) inference methods for prediction. First, we will model the problem in a probabilistic and generic way, taking into account all possible interactions between the variables of interest. In the second part of this thesis, we will develop Bayesian methods for the probabilistic prediction at all stages of the chain. We will propose novel efficient and accurate algorithms, including but not only sequential learning, in order to avoid the need to reprocess all past data every time new data is available.

*WHERE AND WHEN*

One fully funded PhD position is available in Lille from September/October 2018. The thesis will take place jointly at the engineering school IMT Lille Douai and at a fast-growing company focused on machine learning and data science. Earlier start date can be also considered. Lille is a vibrant, young and dynamic city. Lille lies in the heart of the triangle that links three of Europe’s main metropoles: London (80 min), Paris (60 min), and Brussels (35 min).

*WITH WHO*

The students will be supervised by:

- Víctor Elvira: http://pagesperso.telecom-lille.fr/elvira/
- François Septier: http://pagesperso.telecom-lille.fr/septier/

*CANDIDATE PROFILE*

We are looking for a motivated and talented student with:
- background in machine learning, signal processing, statistics or applied mathematics
- strong mathematical skills

-experience in programming, preferably in Matlab and/or Python.

* CONTACT *

If you have any question and/or want to apply, please contact:

- Víctor Elvira: victor.elvira@imt-lille-douai.fr
- François Septier: francois.septier@imt-lille-douai.fr

✔️ @ApplyTime

Hi everyone,

The Institute of Comms and Power Networks in collaboration with the Depart. of Mathematics have a full scholarship for a PhD in the area of anomaly detection for energy security.

If you have the ML skills and a knack for sustainability, then this is the position for you. You will develop and apply ML techniques to increase the energy security of future low-carbon electricity networks!

Due to funder restrictions, the position is open only to EU candidates. The deadline is June 1st, 2018 and the starting date should be in fall 2018.

More information can be found at:

http://www.leeds.ac.uk/info/130558/leeds_doctoral_college/600/global_challenge_doctoral_scholarships

https://engineering.leeds.ac.uk/research-opportunity/2655/big-data-and-energy-security-(leeds-global-challenge-doctoral-scholarship)

Please share with anyone that might be interested.

Best regards,
Petros

—
Petros Aristidou, PhD MEng
Lecturer (Assist. Prof.) in Smart Energy Systems
Institute of Communication and Power Networks,
School of Electronic & Electrical Engineering,
University of Leeds, LS2 9JT, UK

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We are pleased to announce an opening for a postdoc in the lab of Mark van Rossum at the University of Nottingham.

In a EPSRC/ESRC grant on Human-like Computation, we are investigating in the computational role of sleep in cognitive processing and visual reasoning. In particular we are interested in how REM and slow-wave sleep phases map onto processing stages of neurally inspired AI, thereby trying to circumvent some limitations of current deep learning approaches.
This theoretical research is complemented by sleep experiments carried out by the group of Prof Penny Lewis in Cardiff.

The successful candidate will have a PhD (or submitted his/her thesis) and have research experience in either computational neuroscience or machine learning, or a combination of these.

This post is initially a fixed-term contract for a period of 12 months.
As Nottingham is currently creating a Centre for Computational Neuroscience,
long-term independent research positions will open up next year.

Informal enquiries may be addressed to Mark van Rossum. mark.vanrossum-at-nottingham.ac.uk
Formal applications should be made via the website:
https://www.nottingham.ac.uk/jobs/currentvacancies/ref/SCI146218

✔️ @ApplyTime

Several positions (Postdoctoral Fellow/Research Scientist) in neuroimage analysis are available immediately at Stanford University and SRI International. The successful candidate will contribute to research and development in the coherent and robust multi-modal analysis of longitudinal neuroimages collected across multiple sites. The research projects are funded in part by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA; http://www.ncanda.org; 4K MRI sessions), the Adolescent Brain Cognitive Development Study (ABCD; http://addictionresearch.nih.gov/abcd-study; 20K MRI sessions planned) and the National Institute of Mental Health. The researcher will work in a multidisciplinary research environment closely collaborating and publishing with imaging, computer, and neuroscientists at Stanford University and SRI International (see also sibis.sri.com).


Qualifications:
Successful candidates should have a PhD (or equivalent) in Computer Science, Applied Mathematics/Statistics, Electrical or Biomedical Engineering, or related field. Expertise in machine learning and programming is a must. Experience in neuroimage analysis is highly desirable. Being knowledgeable in DTI and fMRI data analysis is a plus.

Please send applications (curriculum vitae and contact information of three references) or questions to kilian.pohl@sri.com

Kilian M. Pohl
Program Director of Biomedical Computing
Center for Health Sciences
SRI International
http://sibis.sri.com/Kilian.Pohl/

✔️ @ApplyTime

Post-doc/PhD positions in Neural Machine Translation (CIS, LMU Munich)

I am expanding my research group, which is located at the Center for Information and Language Processing at the University of Munich (LMU).

Candidates will focus on cutting edge research into using deep learning techniques to solve machine translation (neural machine translation). The group is a well-known machine translation research group with strong interests in related natural language problems. The working language of the group is English, no knowledge of German is required.

Three positions are available (one post-doc position and two PhD student positions), with a target starting date of October 2018. In addition, I am looking for early expressions of interest in a further possible post-doc position (see below).

Position 1 is for a funded full-time post-doc on my European Research Council Starting Grant. 

Position 2 is for a funded full-time PhD student on my European Research Council Starting Grant. 

Position 3 is for a local unfunded PhD student. The candidate is already working externally in the Munich area, and wishes to carry out research for a PhD degree.

I am also looking for early expressions of interest in a possible full-time post-doc in Summer 2019. The candidate should have been working outside of Germany and be interested in moving to Munich in the Summer of 2019. Please contact me for further details. 

All candidates will have possibilities to teach, supervise bachelors/masters students, and to collaborate on grant applications, as appropriate. Post-Docs may also participate in the supervision of doctoral students.

There is significant interaction with the research groups of Hinrich Schütze (deep learning and a variety of NLP problems) and Helmut Schmid (neural machine translation, parsing, tagging, morphology). We also have several active collaborations with colleagues at other universities.

The University of Munich is one of the top research universities in Europe. It was the highest ranked institution on several measures in the Exzellenzinitiative funding program organized by the German national science foundation in 2012.

Munich and the Upper Bavaria area are among the regions in Europe with the highest quality of living. The area is also home to a large number of high-tech, service and manufacturing companies, including many that use NLP technology.

If you are interested in applying please send me:
* a cover letter. Indicate which position you are applying for and include possible starting dates.
* a CV
* a statement of research interests
* (post-doc position): a brief statement of teaching experience and interest
* the names and addresses of two references

If you have questions about these positions please feel free to ask (please include a CV).

LMU is an equal opportunity employer and is committed to increasing the diversity of its staff. We strongly encourage applications from qualified women. Applicants with disabilities will be given preference in case of equally qualified candidates.

Thanks,
Alexander Fraser
--
Prof. Dr. Alexander Fraser
University of Munich (LMU)
Center for Information and Language Processing
Oettingenstrasse 67
80538 Munich
Germany

Email: fraser@cis.uni-muenchen.de
Web: http://www.cis.uni-muenchen.de/~fraser 

✔️ @ApplyTime

OR 2.0 Context-Aware Operating Theaters MICCAI'18 Satellite Workshop Event

Surgical robotic tools and digitally enhanced operating theaters have been giving surgeons a helping hand for years. While they provide great control, precision and flexibility to the surgeons, they don’t yet address the cognitive assistance needs in the operating theater. We are on the verge of a new wave of innovations of artificial intelligence powered, context-aware operating theaters. This workshop aims to highlight the potential use of surgical data science, multidisciplinary approaches and teams with a focus on translation and clinical applications that will define future technologies of the next generation operating theaters.

Please visit our website https://or20.univ-rennes1.frfor more information.

✔️ @ApplyTime

PhD Studentship - Cambridge, UK

Please find below details of a fully funded PhD Studentship with the University of Cambridge, starting in October 2018. 

AI for Megacities: Understanding the impact of climate extremes

Project summary

The student will apply Bayesian statistics and machine learning in new and innovative ways to help transform the field of environmental data science. There is an abundance of data relevant to the forecasting of power demand (e.g., details of the built environment, socio-economic forecasts) and also human health (mortality rates). However, such data are not routinely incorporated into future climate risk projections.

The student will work closely with members of the Cambridge Machine Learning group and help develop a climate downscaling framework (incorporating probability distribution modelling) to improve the representation of high-impact climate events within localised urban environments. It is expected that the student will provide intellectual input into the project design throughout the project, and lead their own research activities on a daily-to-weekly basis.


Requirements

A strong background in engineering, physics, mathematics and/or statistics is essential. The candidate must hold an honors degree graded at least upper second-class (2i), and/or a master's degree in a relevant subject. Experience writing and developing code is highly desirable. Meets UK residency requirements (see here)


More details
https://www.findaphd.com/search/ProjectDetails.aspx?PJID=97521

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The 34th ACM Symposium on Applied Computing (SAC 2019)


St. Raphael Resort, Limassol, Cyprus, April 8-12, 2019


https://www.sigapp.org/sac/sac2019


* Submission Deadline: May 25, 2018 *

✔️ @ApplyTime

24th International Symposium on Methodologies for

Intelligent Systems (ISMIS 2018)


St. Raphael Resort, Limassol, Cyprus, 29-31 October, 2018


http://www.cyprusconferences.org/ismis2018


* Extended Deadline: 28 May, 2018 *

✔️ @ApplyTime

Position
=========================================================
Paid Intern Deep Learning


The major projects include object recognition and detection, anomaly detection, grasp prediction for autonomous robot manipulation, and more. This individual will work as part of Dishcraft’s computer vision team, contributing to algorithm development, data collection and annotation, sensor evaluation, and testing.



About Us
=========================================================

Dishcraft Robotics
San Carlos, CA
http://www.dishcraft.com/

At Dishcraft Robotics, our mission is to build things that matter. We are a venture-backed Bay Area start-up that is revolutionizing robotics, computer vision, machine learning, and mechanical design. Come join our talented team of technologists and business people as we create advanced machines in an industry that touches everyone.

First and foremost, we value people, intellectual engagement, and transparent communication. We are looking for a highly motivated, intellectually curious and passionate Deep Learning Engineer. Dishcraft is developing intelligent robots for commercial kitchens that can help with tedious and dangerous tasks. Our robots need to operate intelligently in chaotic environments to deliver reliability, safety, and high throughput for their tasks.



Details
=========================================================
About The Role

Contribute to developing and testing convolutional neural network (CNN) architectures for object detection and classification for Dishcraft’s robots.
Contribute to developing and managing data collection and annotation processes for diverse machine learning projects.
Perform proof of concept studies by implementing a new architecture or theory for deep learning.
Document and analyze workflows and results.
Evaluate sensors and contribute to developing new sensor technology.
Collaborate closely with roboticists, software engineers, mechanical engineers, test engineers, external consultants from both industry and academia, and robots.

About You

Demonstration of contributions to the field of deep learning: large projects, publications at conferences (CVPR, ICML, NIPS, ICCV, ECCV, ICLR, ICPR, IPMI, and etc.), journal publications, internships for relevant projects, blog posts, open source projects.
BS or higher degree in computer vision or machine learning, or equivalent experience.
Experience implementing deep learning architectures.
Proficiency in Python (particularly, numpy, scipy, pandas, scikit-image, and scikit-learn) and C/C++.
Experience with tools such as Caffe, Torch, Theano or TensorFlow.
Familiarity with data cleaning, analysis, and developing efficient, accurate data annotation schemes.
Familiarity with unit testing and version control.
Familiarity with state-of-the-art CNN architectures such as ResNet, VGG, GoogleNet (Inception), Faster RCNN, and Mask R-CNN.
Highly motivated, team player with strong technical collaboration skills and desire to learn quickly and develop new skills.
The desire to be part of a fast-moving start-up and work in a collaborative environment with few rigid boundaries.


Disclaimer
=========================================================

Dishcraft Robotics is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, national origin, pregnancy status, sex, age, marital status, disability, sexual orientation, gender identity, or any other characteristics protected by law.

To apply, please send an email to matt.shaffer@dishcraft.com referencing this posting in the Machine Learning News Group and complete the application at:

http://www.dishcraft.com/apply/?gh_jid=4013397002

✔️ @ApplyTime

#Culture_Shock

#شک_فرهنگی چیست؟ و چرا باید در تصمیم‌مان برای اپلای حتما بدان بیاندیشیم؟

در آینده در این مورد توضیح خواهیم داد. شما نیز می‌توانید در مورد آن گوگل کنید.

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Postdoc position in machine learning and neuroimage analysis (University of Texas Southwestern, Medical Center, Dallas USA)

✔ @ApplyTime

https://kddfashion2018.mybluemix.net

✔ @ApplyTime

Applications are invited for a postdoctoral fellow position in the computational systems biology lab (http://compbio.uthsc.edu/) at University of Tennessee Health Science Center. The successful candidate will be involved in developing deep learning algorithms for genomics research and precision medicine. The Department of Genetics, Genomics and Informatics and the Center for Integrative and Translational Genomics provide a highly dynamic and collaborative environment fostering scientific breakthroughs. 

The candidate must have obtained his/her Ph.D. degree in Bioinformatics, Computer Science or a related field. We are expecting high motivation and ability to work independently, as well as part of a research team. The candidate must have acquired a solid publication record and have excellent programming skills. Research experience in machine learning is required. Preference will be given to candidates with knowledge of deep learning. 

Please send a CV, a cover letter describing your previous work and career goals, putative starting date and the contact information for three references to Dr. Yan Cui (ycui2@uthsc.edu). 

Salary will be commensurate with relevant experience and is competitive for postdoctoral research fellows. The position includes an excellent benefits package (http://www.uthsc.edu/postdoc/benefits.php). Located in Memphis, a dynamic Mid-South city rich in culture, history, diversity, music and cuisine, the University of Tennessee Health Science Center is one of the largest, most comprehensive academic health centers in the United States with a solid commitment to postdoctoral training. UTHSC is an EEO/AA/Title VI/Title IX/Section 504/ADA/ADEA/V institution in the provision of its education and employment programs and services. 

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