Question 1

Does ApplyKite only list funded positions?

Accepted Answer

Yes, we prioritize fully funded and partially funded opportunities.

Question 2

Why is access to professors' social network posts important?

Accepted Answer

Many great opportunities are never widely advertised. ApplyKite helps you find these hidden positions, significantly increasing your chances of getting accepted.

Question 3

Do I need to cold email professors for European universities, which are mostly position-based?

Accepted Answer

In Europe, many PhD and postdoc positions are publicly listed, but cold emailing can still be valuable. Professors may have hidden funding or future openings and could consider you for them.

Question 4

Which countries and fields of study does ApplyKite support?

Accepted Answer

ApplyKite provides opportunities in most research-focused countries like the US, Canada, UK, Europe, Australia, Asia and etc and covering all fields in engineering, natural sciences, social sciences, and etc.

Question 5

Can I use ApplyKite for Master’s, PhD, and postdoc applications?

Accepted Answer

Yes! ApplyKite helps students at all levels—master’s, PhD, and postdoc—find professors, funding, and research opportunities.

Question 6

How does ApplyKite help me secure a fully funded position?

Accepted Answer

ApplyKite was built by people who have gone through the application process and understand its challenges. We help by: - Providing a curated list of open fully funded positions in your field. - Offering a searchable professor database that highlights those with active grants. - Helping you write effective emails, CVs, and SOPs tailored to each opportunity.

Question 7

Why is direct communication with professors better than just applying to open positions?

Accepted Answer

If a professor is impressed by your profile, they may offer you scholarships, research positions, or recommend you to colleagues—even if no open position is advertised.

Question 8

What is the best strategy for getting a professor’s attention?

Accepted Answer

A well-crafted email, a customized CV, and a research-focused approach are key. ApplyKite helps generate personalized email templates to improve your chances.

Question 9

What documents do I need to apply?

Accepted Answer

Most applications require a CV, Statement of Purpose (SOP), academic transcripts, recommendation letters, and sometimes a research proposal.

Question 10

Can I get a fully funded opportunity without publications?

Accepted Answer

Yes! Many students secure fully funded positions with direct communications with fitted professors, strong research potential, skills, and a compelling CV/SOP rather than just publications.

Question 11

Can I get fully funded admission with a low GPA?

Accepted Answer

Yes! A lower GPA can be compensated with strong research experience, excellent recommendations, and a well-written CV/SOP and also by attracting a professor attention through cold emailing.

Question 12

What IELTS/TOEFL score do I need? Should I pass the exam before applying?

Accepted Answer

Requirements vary by university and some universities waive the test if your previous degree was in English. Some universities gives you conditional offer to meet the requirement later as well. Also, you do not need to have your score while cold emailing. You can start contacting potential professors with your CV and then get the required score.

Explore Master’s Positions in computer science in germany

Master Positions in computer science in germany

Contentious Politics in the Digital Age

Contentious Politics in the Digital Age

Machine Learning

Machine Learning

Machine Learning

Machine Learning

Your Path, Mapped Out

Find a Professor

Reach Out

Prep & Apply

Book The Flight

Start Your Chapter

What Students Usually Ask

Before You Apply for Master’s in computer science in germany

Exams

Funding

Deadlines

Visas

Explore other paths

Master Positions in computer science in germany

Contentious Politics in the Digital Age

Contentious Politics in the Digital Age

Machine Learning

Machine Learning

Machine Learning

Machine Learning