Usually when you apply anywhere you need to fulfill some specific kind of requirements which usually include writing a formal application, letter of motivation, research proposal etc. Usually it is hard for grad students to write a crisp, clean and clear letter of motivation. To be honest, you may find several posts on the internet which do tell you how to write professionally. They are good enough to clearly tell you what points should be included, what not and many other things to learn about professional writing. Still, when I look back at my graduation days, I know even after reading many instructions I was not able to write ‘to-the-point’. According to me , writing skill is not something that you can part in binary like- ‘I write perfectly’ or ‘I can not write even a word’. It is something that you learn and get better with the the time. So, I am not going to pin-point the suggestions because you can get it many where but some ‘to-the-point’ things which you may use directly in your letter.

Ideas and main points

Start with writing down some of the main ideas, important points you would like to approach in your letter and later build around them, enrich their content; an example would be :

1. Make your goal clear; provide a short preview of the rest of the letter;
2. Why do you think that the university and the Master's program are interesting and suitable for you? ;
3. Focus on some of your strongest qualifications, past experiences (international experiences are always relevant) and qualities; organise the middle paragraphs in terms of the qualifications most relevant to the programme, you can also refer to your CV for more details;
4. Conclude by restating your interest and show appreciation for the chance to prove yourself in the letter (in some cases you can ask for a personal interview)

How to start-
Your very first line should not be just a line but an impression and reference. None would want to read you unless he knows what it is about. Just like this post. If I would not have written that it is about writing a motivation-letter, you probably would not get annoyed. So start by writing what your letter is about. It could seem like this-

Letter Of Application

Your Address And Contact Details

Receiver’s Address

Dear XYZ

I would like to apply for the…..

or

I am writing here to apply for the…

or

This is regarding your advert. published….

Then Tell Background like-
As my resume reveals, I have Bachelor`s degree from XYZ University and currently, I am…..

Be sure to signify your institution/University like-
I am privileged to obtain my postgraduate education in Bioinformatics at XXX which is known for its enriching academic ambiance where learning and research complement each other.

Then tell about your professional experience like-
Being taught by eminent faculty, I have developed a big interest and passion towards Bioinformatics and managed to have a strong foundation in ……

After that tell how this position would help you, like-
The opportunity to participate in this study would foster….

Assure them that you will make use of whatever you learn there, like-
I plan to ensure the further dissemination of the knowledge and experience gained by this opportunity in…

Close the letter with usual formality, like-
I, hereby enclose a copy of my CV/Resume (whatever it is, there is a difference we all know it) with the hope of consideration. Looking forward to hearing from you.

All the things written above is just my view. You still should see and learn which can be done by one thing and that is -reading about it. Then , please try to write yourself, do not copy /paste. Whatever is written in the post is just to have an idea about the things that should be included in the letter of motivation. You need to write accordingly with a wise choice of words.
Hope this was helpful. You may comment or ask anything if you want to.

The most common newbie questions are:

Should I try to use these free open source programs?  Why are we not trying GUI software for computational analysis? Should I use commercial bioinformatics programs/software?”

1. Let’s be open

We generally think free and cheap are useless. But this concept is not applicable when we discuss open source software. Mostly, the bioinformatics software is developed by highly competitive biological programmers who believe in open sharing of knowledge. They come under Open Bioinformatics Foundation or O|B|F which is a non-profit, volunteer run organization focused on supporting open source programming in bioinformatics. The best part about open source tools/software is that they’re free to download the source code and read exactly what the program does. If you are so inclined, you can view all of the parts of the program and see the logical flow of the pipeline. In addition, open source makes an excellent learning tool for any beginning bioinformatician. Moreover, you can modify existing open source programs to deal with cutting-edge problems or to customize your pipeline. Apart from your computational and analysis work, most of the reviewer also prefers the open source based results so that they can validate the results if validation required.

2. Code headache

As a bioinformatician you are supposed to know the basics of programming languages, and if you are not good at it, then please learn it as soon as possible because you are not a bio-analyst but biological programmers. The open source programs usually lack dedicated service and support teams (often because they were the product of an overworked doc/postdoc!) so you are responsible for troubleshooting your own errors most of the time. We commonly receive the HELP email to support and assist to setup the pipeline; you can also find this kind of request on any QA forum. I personally believe this coding horror brings the biggest downside of open-source programs; where you need some programming skills in order to implement the program in your pipeline. But, if you are not able to fix the pipeline and modify the open source code according to your requirements them you should re-think on your bioinformatician name tag!!!

3. Dive into the codes

Some of the biologist turn bioinformatician says “if you can do the same thing with commercial software then why to get migraine with weird codes”, well this statement looks to me that guys are keen to learn swimming but still don’t like to get wet. If you are still using paid software and doing your work by customer support and clicking some of the well-designed GUI button then perhaps you are not interested in learning and trying new and challenging bioinformatics works. You are missing the basic flavour of bioinformatics. Let’s dive into the coding world, I am sure your will enjoy it. I recommend your to swim freely in code’s sea, and enjoy the journey; do not merely watch it from the outside.  

4. Paid does not mean better

The bioinformatics company which are specializes in bioinformatics solutions develop well designed/packed, user friendly software by using a large number of specialised scientist, programmers and support staff. They also provide good services to accomplice your biological analysis work. This means that if you hit a ‘snag’ with your data, help is likely only a phone call away! These companies price their products competitively against the cost of a dedicated bioinformatician. You may be able to afford the program, but not the additional staff! Additionally, most of the functionality that you need in your analysis is already coded into the program. Need to plot a graph? Just click this button right here. It is that easy. But, as a bioinformatician this is not generally well encouraged approach in biological analysis work, because the software is not available to everyone and your data can’t be validated. Moreover, there is very less chances that anyone will repeat your work or love to do similar kind of research (because not all the labs in the world are rich like yours).

5. Take a caution

In biological analysis work, in which you deal GB/TB of data are having maximum chances of getting errors, so please be careful and always cross check your data before coming to any conclusion. Even an error in two line code can alter your entire analysis and display weird results. Some of the scientist blindly believes on commercial software, which is entirely wrong. Using proprietary tools does not absolve you of the need to actually read and research the type of analysis that you are doing. This is particularly true in the case of genome assembly and annotation.

At the end, I would like to tell only one think that open source solutions allows you to do more cutting edge analysis than the commercial tools. So let’s go for it.

Disclaimer:

This is my personal view. I have nothing to do with any company or open source community. The views expressed on these pages are mine alone and not those of my current/past employers. I do reserve the right to remove comments left by spammers or off-topic comments.

Dr. Rawal and his US based collaborators have recently secured grant for development of vaccine against an infectious disease agent. For this project, applications are invited for the posts of Junior Research Fellow (two positions) for the following time-bound sponsored projects as per the details given below:

PI: Dr. Kamal Rawal, Biotechnology Department, JIIT, Noida.

Post: JRF (Two)

Job Description: Bioinformatics analysis, Software development, Programming, Text Mining, Deep Curation

Duration: The post is valid upto duration of the project. Continuation is subject to satisfactory performance.

Emoluments depends upon experience and skill sets. We will hire them on following scale:

Junior Scale- Level 1: Rs 22000 per month.

Senior Scale - Level 2: Rs 30000 per month.

Essential Qualification(s) for JRF post:

(A) A Master degree (MSc or MTech or equivalent with minimum of 55% marks) in Bioinformatics/Computer Sciences, IT, Life Sciences, Physical Sciences, Chemical Sciences, Mathematical Sciences or Statistics, Agriculture, Veterinary, Medicine, Pharmacy, Engineering & Technology from a recognized University/Institute and having some experience/skills in bioinformatics, programming, computational or software development work.

(B) In exceptional cases, we can also consider candidates with B. Tech or equivalent with right skill sets and experience for the post of JRFs.

Desirable:

A) Preference will be given to BINC (Bioinformatics National Certification)/DBT-BET/ICMR/ CSIR /UGC/ JRF/ NET qualified candidates. However, Non- NET qualified candidates can also apply.
B) Candidates who have worked with programing, text mining, NGS data analysis etc are encouraged to apply.
Updated resume including a cover letter (preferably by E. mail) should be mailed to bioinfocvatgmaildotcom, and Dr. Kamal Rawal at kamaldotrawalatgmaildotcom. Short listed candidates would be called for interview. No TA/DA will be paid to the candidates called for interview.

Candidate may also fill the following form:

https://docs.google.com/…/1FAIpQLSdZoZ21ZoNRStEeL5…/viewform

Or

http://tinyurl.com/bioinfocv2017

Genomics England will play a key role in building on the UK’s long track record as leader in medical science advances to push the boundaries by unlocking the power of DNA data. The UK will become the first ever country to introduce this technology in its mainstream health system – leading the global race for better tests, better drugs and above all better, more personalised care.

http://www.genomicsengland.co.uk/100k-genome-project/

http://statbio.github.io

SciGenom Research Foundation (SGRF) and Institute of Genomics and Integrative Biology (IGIB) are pleased to host the Next-Generation Sequencing and Bioinformatics for Genomics & Healthcare conference.

In the ten years since the first human reference genome was completed for US$3 billion the sequencing technologies have radically changed leading to great reduction in sequencing cost. Today a human genome can be sequenced for under US$ 5000 in less than two weeks. It is expected that by the end of 2015 the cost of sequencing a human genome will drop to below thousand dollars. The next generation sequencing technologies over the past five years have enabled a large number of genomic studies that impact human health and disease. Also, this has made possible the growth of microbial, animal and plant genomics studies. While the data production has increased at a rapid pace challenges remain in analyzing and understanding the data. The conference will cover the next generation sequencing (NGS) technologies, bioinformatics for NGS and applications of NGS in many areas including personalized medicine.

For more info : http://www.scigenomconferences.com/2013/default.php

Address of the bookmark: https://bioconda.github.io/recipes/snakemake/README.html

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.

To read more about this collaboration, visit: https://edu.t-bio.info/pine-biotech-joins-forces-with-the-bioclues-organization-to-promote-bioinformatics/