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<channel>
	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/35805?offset=200</link>
	<atom:link href="https://bioinformaticsonline.com/related/35805?offset=200" rel="self" type="application/rss+xml" />
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9242/check-the-size-of-a-directory-free-disk-space</guid>
	<pubDate>Mon, 17 Mar 2014 02:35:32 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9242/check-the-size-of-a-directory-free-disk-space</link>
	<title><![CDATA[Check the Size of a directory &amp; Free disk space.]]></title>
	<description><![CDATA[<p>The amount of databases we bioinformatician deal are just HUGE &hellip; In such cases, we always need to check our server for free spaces etc. I planned this article to explains 2 simple commands that most bioinformatician want to know when they start using Linux / BioLinux. First: Size of a directory (du) and and second: free disk space that exists on your machine (df).</p><p><br /><strong>'du' &ndash; Check the size of a directory</strong></p><p><br />$ du<br />This command ( du) gives you a list of directories that exist in the current working directory along with their sizes in kilobytes (default). The last line of the output gives you the total size of the current directory including its subdirectories. <br /><br />$ du /home/jin1<br />The above command would give you the directory size of the directory /home/david<br /><br />$ du -h<br />The same &ldquo;du&rdquo;command with some flag gives you a better output than the default one. The option '-h' stands for human readable format. Therefore, in order to print the sizes of the files / directories in your desire notation use this time suffixed with a 'k' if its kilobytes and 'M' if its Megabytes and 'G' if its Gigabytes.<br /><br />$ du -ah<br />If you are interested in checking everything present in a folder use above mentioned command. It gives us not only the directories but also all the files that are present in the current directory. The &ldquo;-a&rdquo; flag displays the filenames along with the directory names in the output. <br /><br />$ du -c<br />This gives you a grand total as the last line of the output. So if your directory occupies 30MB the last 2 lines of the output would be 30M.<br /><br />$ du -s<br />Use this command to displays a summary of the directory size. It is the simplest way to know the total size of the current directory.<br /><br />$ du -S<br />This would display the size of the current directory excluding the size of the subdirectories that exist within that directory. So it basically shows you the total size of all the files that exist in the current directory.<br /><br />$ du --exculde=mp3<br />Several times it required to exclude some directory in our size calculation. In such cases the above command would display the size of the current directory along with all its subdirectories, but it would exclude all the files having the given pattern present in their filenames.</p><p><br /><strong>'df' - finding the disk free space / disk usage</strong><br /><br />$ df<br />Hmmm &hellip; now &ldquo;df&rdquo; command is really useful, and I guess you are going to use it over time. Typing the above command, outputs a table consisting of 6 columns. All the columns are very easy to understand. Remember that the 'Size', 'Used' and 'Avail' columns use kilobytes as the unit. The 'Use%' column shows the usage as a percentage which is also very useful.<br /><br />$ df -h<br />Displays the same output as the previous command but the '-h' indicates human readable format. Hence instead of kilobytes as the unit the output would have 'M' for Megabytes and 'G' for Gigabytes.<br /><br />Example: Linux installed on /dev/hda1<br />$ df -h | grep /dev/hda1</p><p><br />All right, this is not the only option to check the sizes and free spaces but there are a few more options that can be used with 'du' and 'df' . I will discuss it later.<br /><br /></p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9441/jrf-at-gautam-buddha-university</guid>
  <pubDate>Thu, 27 Mar 2014 03:53:57 -0500</pubDate>
  <link></link>
  <title><![CDATA[JRF at Gautam Buddha University]]></title>
  <description><![CDATA[
<p>Gautam Buddha University (GBU) Noida invites applications for the follow posts<br />2014 March Advertisement from Gautam Buddha University (GBU)<br />Junior Research Fellow (JRF)<br />No. of Positions:  01<br />Educational Qualifications:<br />Master degree in any discipline of Life Science with NET qualified or valid GATE score. Desirable Qualification: Preference will be given to candidates having research experience in Bioinformatics<br />Experience:</p>

<p>(details of experience required)<br />Pay Scale:<br />INR Rs.12000/-P.M. + HRA<br />Category:<br />Science and Research Jobs<br />How To Apply:<br />The interested candidates should report for the Interview on 31st<br />March, 2014 at 10:00 am in the Conference Room of Dean, School of Biotechnology, First floor, Gautam Buddha University, Greater<br />Noida. Interested candidates may also send their resume to undersigned by post-mail/e-mail shaktis@gbu.ac.in or shaktisahi@gmail.com. No TA and DA will be paid for appearing for the interview<br />Download Official Notification:</p>

<p>http://www.gbu.ac.in/Recruitment/JRF_advertisement_DSTProject_Shakti_24March14.pdf</p>
]]></description>
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/9598/junior-research-fellowship-at-gb-pant-university</guid>
  <pubDate>Thu, 03 Apr 2014 12:29:46 -0500</pubDate>
  <link></link>
  <title><![CDATA[Junior Research Fellowship at G.B. PANT UNIVERSITY]]></title>
  <description><![CDATA[
<p>DEPARTMENT OF MOLECULAR BIOLOGY &amp; GENETIC ENGINEERING<br />COLLEGE OF BASIC SCIENCE AND HUMANITIES<br />G.B. PANT UNIVERSITY OF AGRICULTURE AND TECHNOLOGY<br />PANTNAGAR -263145, UTTARAKHAND</p>

<p>No. CBSH/MBGE/356</p>

<p>Subject: Advertisement for the award of Junior Research Fellowship.</p>

<p>Applications are invited for award of one Junior Research Fellowship on a consolidated fellowship of Rs. 12,000/- pm in the project “Bioinformatics Sub-DIC ”, under the Coordinatorship Dr. Anil Kumar. The fellowship is purely temporary and may continue till the duration of the project or maximum three years which ever is earlier. The appointment shall be given on six monthly review basis.</p>

<p>ESSENTIAL QUALIFICATION</p>

<p>M.Sc. Bioinformatics having research experience on In silico experimentation.</p>

<p>Candidates possessing the above qualifications may submit their application on<br />plain paper in the following format to the undersigned latest 18 April, 2014 the interviews will be held on 19 April, 2014 at 11.00 AM in the office of the undersigned. No separate letter for interview will be issued or any TA/DA will be paid for attending the interview.</p>

<p>Advertisement: http://www.gbpuat.ac.in/01042014_18april14_Advertisement%20for%20JRF%20Position,%20BI.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10415/bioinformatician-stuck-in-wet-lab</guid>
	<pubDate>Tue, 06 May 2014 12:46:56 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10415/bioinformatician-stuck-in-wet-lab</link>
	<title><![CDATA[Bioinformatician stuck in wet-lab]]></title>
	<description><![CDATA[<p>This guide is aimed at pet bioinformaticians, and is meant to guide them towards better career development.</p>
<p><strong>1. Make friends with local bioinformatics groups</strong><br> <strong>2. Talk to your computing group</strong><br> <strong>3. Obtain clear expectations</strong><br> <strong>4. Rewrite your job description</strong><br> <strong>5. Papers</strong><br> <strong>6. Attend bioinformatics meetings</strong><br> <strong>7. Try first, ask later</strong></p><p>Address of the bookmark: <a href="http://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/" rel="nofollow">http://biomickwatson.wordpress.com/2013/04/23/a-guide-for-the-lonely-bioinformatician/</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/43681/a-guide-to-machine-learning-for-biologists</guid>
	<pubDate>Tue, 28 Dec 2021 01:43:25 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/43681/a-guide-to-machine-learning-for-biologists</link>
	<title><![CDATA[A guide to machine learning for biologists]]></title>
	<description><![CDATA[<p>Because of the increasing size and inherent complexity of biological data, there has been an increase in the application of machine learning in biology to create useful and predictive models of the underlying biological processes. All machine learning techniques fit models to data; nevertheless, the specific methods are highly variable and can appear baffling at first glance. In this Review, we hope to give readers a moderate introduction to a few fundamental machine learning techniques, including the most recently created and frequently used deep neural network techniques. We illustrate how different algorithms may be adapted to specific types of biological data, as well as some best practises and points to consider when embarking on machine learning studies. There is also discussion of several upcoming directions in machine learning methodology.</p><p>Address of the bookmark: <a href="https://www.nature.com/articles/s41580-021-00407-0" rel="nofollow">https://www.nature.com/articles/s41580-021-00407-0</a></p>]]></description>
	<dc:creator>Abhi</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/43898/online-resources-on-must-read-papers-in-evolutionary-biology-for-a-literature-club</guid>
	<pubDate>Tue, 28 Jun 2022 07:29:08 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/43898/online-resources-on-must-read-papers-in-evolutionary-biology-for-a-literature-club</link>
	<title><![CDATA[Online resources on must-read papers in evolutionary biology, for a literature club]]></title>
	<description><![CDATA[<pre>1.       *Nick Barton:*

- The textbook "Evolution" by Nick Barton, with resources for
  exploring the literature: Barton, N. H., Briggs, D. E. G., Eisen, J.
  A., Goldstein, D. B., &amp; Patel, N. H. (2007). Evolution. Cold Spring
  Harbor Laboratory Press.

- Papers from a course named "Classics in Evolutionary Biology":

Evolutionary Synthesis
1. Haldane, J. B. S. 1932. The causes of evolution. Longmans. New York.
   (esp. Ch. IV).
2. Fisher, R. A. 1930. The genetical theory of natural selection. Oxford
   University Press, Oxford. Selected Sections - Fundamental Theorem.

Genetic Variation
1a. Lewontin, R. C., and J. L. Hubby. 1966. A molecular approach to
the study of genic heterozygosity in natural populations. II. Amount
of variation and degree of heterozygosity in natural populations of
Drosophila pseudoobscura. Genetics. 54:595-609.

1b. Sachidandam et al. 2001. A map of human genome sequence variation
containing 1.42 million single nucleotide polymorphisms. 409: 928-33.

2. Wright S., Dobzhansky T., Hovanitz W. 1942 Genetics of natural
populations VII The allelism of lethals in the third chromosome of
Drosophila pseudoobscura. Genetics 27: 363-394.

Recombination and evolution
1. Hill, W. G., and A. Robertson. 1966. The effect of linkage on limits
to artificial selection. Genet. Res. 8:269-294.

2. Maynard Smith and Haigh. 1974. The hitch-hiking effect of a favourable
gene. Genet. Res. 23: 23-35.

Understanding sequence variation
1. Begun D. J., Aquadro C. F., 1992 Levels of naturally occurring DNA
polymorphism correlate with recombination rate in Drosophila melanogaster.
Nature 356: 519-520.

2. Green R. E., Reich D., P&auml;&auml;bo S., 2010 A draft sequence of the
Neandertal genome. Science 328: 710-722.

Quantitative Genetics:  variation in complex traits
1. Galton F., 1877 Typical laws of heredity. Nature 15: 492-495-
512-514- 532-533.

2. Turelli M., 1984 Heritable genetic variation via
mutation-selection balance: Lerch's Zeta meets the abdominal
bristle. Theor. Popul. Biol. 25: 138-193.

Quantitative Genetics:  finding the genes
1. Shrimpton A. E., Robertson A., 1988 The Isolation of polygenic factors
controlling bristle score in Drosophila melanogaster II Distribution of
third chromosome bristle effects within chromosome sections. Genetics
118: 445-459.

2. Boyle E. A., Li Y. I., Pritchard J. K., 2017 An expanded view of
complex traits: from polygenic to omnigenic. Cell 169: 1177-1186.

Neutral Evolution
1. Kimura, M. 1968. Evolutionary rate at the molecular level. Science.
217:624-626.

2a. Kern A. D., Hahn M. W., 2018 The Neutral Theory in Light of Natural
Selection. Molecular Biology and Evolution 110: 21077-6.

2b. Jensen J. D., Payseur B. A., Stephan W., Aquadro C. F., Lynch M.,
Charlesworth D., Charlesworth B., 2018 The importance of the Neutral Theory
in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 112:
2109-4.

2c. Ellegren &amp; Galtier. 2016. Determinants of genetic diversity. Nature
Reviews Genetics.

Mutation and Genetic Variability
1. Luria, S. E., and M. Delbr&uuml;ck. 1943. Mutations of Bacteria from Virus
Sensitivity to Virus Resistance. Genetics. 28(6):491-511.

2. Hill, W G. 1982. "Rates of Change in Quantitative Traits From Fixation
of New Mutations." Proceedings of the National Academy of Sciences (U.S.A.)
79: 142-45.

Testing for selection
1. McDonald &amp; Kreitman. 1991. Adaptive protein evolution at the Adh locus
in Drosophila. Nature.

2. Begun, et al. Mol. Biol. Evol. 16, 1816-1819 (1999).

3. Siddiq et al. 2016. Experimental test and refutation of a classic case
of molecular adaptation in Drosophila melanogaster.  Nature Ecology &amp;
Evolution.

The shifting balance
1. Wright, S. 1932. The roles of mutation, inbreeding, crossbreeding and
selection in evolution. Proceedings of the VI International Congress of
Genetics: 1. pp 356-366.

2. Coyne, J.A., N.H. Barton, and M. Turelli. 1997. A critique of Wright's
shifting balance theory of evolution.  Evolution 51: 643-671.

3. Barton. 2016. Sewall Wright on Evolution in Mendelian Populations and
the "Shifting Balance". Genetics.

Evolution of Sex
1.  Muller, H.J. 1964. The relation of recombination to mutational advance.
Mutation Res. 1(1):2-9

2. McDonald et al. 2016. Sex speeds adaptation by altering the dynamics of
molecular evolution. Nature.

Kin Selection, Cooperation, and Conflict
1. Hamilton, W. D. 1964. The genetical evolution of social behaviour I.
Journal of Theoretical Biology. 7:1-52.

2. Trivers, R. L. 1974 Parent-offspring conflict. American Zoologist.
14(1):249-264.

Sexual Selection
1. Zahavi, A. 1975. Mate selection - a selection of a handicap. J. Theor.
Biol. 53:205-214.

2. Kirkpatrick, M., and Ryan, M.J. 1991. The evolution of mating
preferences and the paradox of the lek. Nature. 350:33-38.

Fitness Landscapes
1. Dean, A. 1995. A Molecular Investigation of Genotype by Environment
Interactions. Genetics. 139:19-33.

2. Costanzo et al. 2010. The Genetic Landscape of a Cell. Science.

Speciation
1. Coyne, J. A., and H. A. Orr. 1989. Patterns of speciation in Drosophila.
Evolution. 43:362-381.

2. Corbett-Detig et al. 2013. Genetic incompatibilities are widespread
within species. Nature.

2.       *Marcos Antezana:*

Valen, L. v. 1975. Energy and Evolution. University of Chicago, Department
of Biology.

3.       *Remco Folkertsma:*

1. The work by Hopi Hoekstra on local adaptation and oldfield mice

2. Poelstra, J. W., Vijay, N., Bossu, C. M., Lantz, H., Ryll, B., M&uuml;ller,
I., ... &amp; Wolf, J. B. (2014). The genomic landscape underlying phenotypic
integrity in the face of gene flow in crows. Science, 344(6190), 1410-1414.

4.       *Joshka Kaufmann and Leslie Turner*

They offer us a link to 'papers every evolutionary biologist should read',
the papers are collected by Leslie Turner.
https://static1.squarespace.com/static/53e8cb7ce4b02c4bc3aeeee4/t/5ab8fcb670a6ad55c67fcdf4/1522072758665/EvoBioClassicsRefList.pdf

5.       *Sarah Stockwell*

Matt Ridley collected classic papers in evolutionary biology and printed
part of these papers in his book Evolution (see Matt Ridley. Evolution
(Univ. of Oxford Press, 2nd edition, 2004))</pre>]]></description>
	<dc:creator>Shruti Paniwala</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server</guid>
	<pubDate>Fri, 06 Jun 2014 16:18:43 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11582/monitor-running-jobs-on-linux-server</link>
	<title><![CDATA[Monitor running jobs on Linux server]]></title>
	<description><![CDATA[<p>You as a bioinformatican run lots of program on your servers. Sometime the shared server is also used by your colleague. If server is busy you sometime need to check the running programs and want to monitor the running programs as well. The "top" command will come in handy when you need to find out if things are still running, how long they&rsquo;ve been running, or how much memory is being used.<br /><br />&lsquo;top&rsquo; is very simple to run: type<br /><br />%% top<br /><br />You&rsquo;ll get a screen that looks like this, and is updated regularly:<br /><br /><img src="http://bioinformaticsonline.com/mod/photo/top.png" width="659" height="582" alt="image" style="border: 0px;"><br />Simple, right? Heh.<br /><br />First! Note that you can use &lsquo;q&rsquo; or &lsquo;CTRL-C&rsquo; to exit from &lsquo;top&rsquo;.<br /><br />Now let&rsquo;s read and understand at each line independently.<br /><br />The first line:<br /><br />top - 23:00:48 up 39 days,&nbsp; 2 user,&nbsp; load average: 0.00, 0.00, 0.00<br /><br />The first line tells you the current time, how long the machine has been up, how many users are logged in, and the short/medium/long-term compute load on the machine. If you run something for a long time, you&rsquo;ll see these numbers go up. Right now, the machine is basically just sitting there, so these are all close to 0.<br /><br />The second line:</p><p>Tasks:&nbsp; 239 total,&nbsp;&nbsp; 1 running,&nbsp; 238 sleeping,&nbsp;&nbsp; 0 stopped,&nbsp;&nbsp; 0 zombie<br /><br />This line tells you how many processes are running. If you are using laptops machines it&rsquo;s not so interesting because you really are the only one using this machine.<br /><br />Cpu(s):&nbsp; 0.0%us,&nbsp; 0.0%sy,&nbsp; 0.0%ni,100.0%id,&nbsp; 0.0%wa,&nbsp; 0.0%hi,&nbsp; 0.0%si,&nbsp; 0.0%st<br /><br />This line contains the CPU load. The first two numbers are how busy the system is doing computation (&ldquo;us&rdquo; stands for &ldquo;user&rdquo;) and how busy the system is doing system-y things like accessing disks or network (&ldquo;sy&rdquo; stands for &ldquo;system&rdquo;). We&rsquo;ll talk more about this later.<br /><br />Mem:&nbsp;&nbsp; 49457320k total,&nbsp;&nbsp;&nbsp; 3492174k used,&nbsp; 14535596k free,&nbsp;&nbsp;&nbsp; 1435148k buffers<br /><br />This should be easy to understand &ndash; how much memory you&rsquo;re using! <br /><br />Swap:&nbsp;&nbsp; 539356k total,&nbsp;&nbsp; 28332k used,&nbsp;&nbsp; 836562k free,&nbsp;&nbsp;&nbsp; 29862014k cached<br /><br />Swap is just on-disk memory that can be used to &ldquo;swap&rdquo; out programs from main memory. Again, we&rsquo;ll talk about this later.:<br /><br />PID USER&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; PR&nbsp; NI&nbsp; VIRT&nbsp; RES&nbsp; SHR S %CPU %MEM&nbsp;&nbsp;&nbsp; TIME+&nbsp; COMMAND<br />&nbsp; 1 root&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 39 &nbsp; 19&nbsp; 0&nbsp; 0&nbsp; 0 S&nbsp; 0.0&nbsp; 0.0&nbsp;&nbsp; 246:57.22 kipmi0<br />&nbsp; 2 root&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; RT&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp; 0&nbsp;&nbsp;&nbsp; 0 S&nbsp; 0.0&nbsp; 0.0&nbsp;&nbsp; 0:00.00 migration/0<br /><br />And... finally! What&rsquo;s actually running! The two most important numbers are the %CPU and %MEM towards the right, as well as the COMMAND. This tells you how compute- and memory-intensive your program is. Right now, nothing&rsquo;s running so the numbers aren&rsquo;t very interesting, but just wait until we run something...</p>]]></description>
	<dc:creator>Jitendra Narayan</dc:creator>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</guid>
	<pubDate>Sun, 01 Jun 2014 23:40:14 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/11355/genomics-and-personalized-medicine-breakthroughs</link>
	<title><![CDATA[Genomics and Personalized Medicine Breakthroughs]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/VAR-1vNc0TE" frameborder="0" allowfullscreen></iframe>http://bit.ly/e8QGzY Human genome mapping is now enabling a breakthrough in medical innovation -- personalized medicine. What does this mean for patients? We can now identify predispositions to disease, predict how we metabolize drugs, and figure out what kinds of treatments we may respond to, and even determine when a drug may give us an adverse reaction. All medical specialties benefit from human genome intelligence -- oncology saw the first impacts -- but advances are now being seen in cardiology, obstetrics and gynecology, pediatric diseases, gastroenterology, rheumatology, immunology and other areas. This video covers the areas that genetic medicine is impacting and where the future of genomic medicine is heading.]]></description>
	
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/33398/tiny-python36-notebook</guid>
	<pubDate>Sat, 03 Jun 2017 03:16:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/33398/tiny-python36-notebook</link>
	<title><![CDATA[Tiny Python3.6 Notebook]]></title>
	<description><![CDATA[<p><span>This is not so much an instructional manual, but rather notes, tables, and examples for Python syntax. It was created by the author as an additional resource during training, meant to be distributed as a physical notebook. Participants (who favor the physical characteristics of dead tree material) could add their own notes, thoughts, and have a valuable reference of curated examples.</span></p><p>Address of the bookmark: <a href="https://github.com/mattharrison/Tiny-Python-3.6-Notebook/blob/master/python.rst" rel="nofollow">https://github.com/mattharrison/Tiny-Python-3.6-Notebook/blob/master/python.rst</a></p>]]></description>
	<dc:creator>Neel</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/11656/faculty-post-at-zhejiang-university</guid>
  <pubDate>Tue, 10 Jun 2014 03:40:40 -0500</pubDate>
  <link></link>
  <title><![CDATA[Faculty post at Zhejiang University]]></title>
  <description><![CDATA[
<p>Zhejiang University (ZJU) is seeking faculty candidates for its newly launched, highly competitive and well funded “Hundred Talents Program”. This search covers all colleges and departments at ZJU. Applicants, expected to be about 35 years old, should hold PhD degree, and postdoctoral experiences are preferred for applicants in most fields. Applicants should have demonstrated commitment to excellence in teaching and research at a level comparable to the academic achievement of assistant professor or associate professor in world-renowned universities. Successful candidates must work full-time and are expected to establish internationally competitive and independent research program in cutting-edge areas of the relevant field at ZJU.</p>

<p>As one of the leading research-intensive universities in China, ZJU is located in the beautiful city of Hangzhou. Successful candidates will be employed as Principal Investigators and are qualified to supervise doctoral students. ZJU will offer an internationally competitive salary and the opportunity to purchase university's apartment at a price much lower than the market price, and will provide office and laboratory spaces as well as internationally competitive research startup packages.</p>

<p>Qualified applicants are strongly encouraged to submit their applications electronically to tr@zju.edu.cn. Applicants should include the following materials in pdf format: a comprehensive CV, a statement of research and teaching plan, and a list of 3 to 5 references with detailed contact information.</p>

<p>Contact：Talents Office, ZJU</p>

<p>Tel：+86-571-88981345, +86-571-88981390</p>

<p>Fax：+86-571-88981976</p>

<p>E-mail:tr@zju.edu.cn</p>
]]></description>
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