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A farmer and his son had a beloved stallion who helped the family earn a living. One day, the horse ran away and their neighbours exclaimed, “Your horse ran away, what terrible luck!”

The farmer replied, “Maybe.”

A few days later, the horse returned home, leading a few wild mares back to the farm as well. The neighbours shouted out, “Your horse has returned, and brought several horses home with him. What great luck!”

The farmer replied, “Maybe.”

Later that week, the farmer’s son was trying to break one of the mares and she threw him to the ground, breaking his leg. The villagers cried, “Your son broke his leg, what terrible luck!”

The farmer replied, “Maybe.”

A few weeks later, soldiers from the national army marched through town, recruiting all the able-bodied boys for the army. They did not take the farmer’s son, still recovering from his injury. Friends shouted, “Your boy is spared, what tremendous luck!”

To which the farmer replied, “Maybe.”

IMPORTANT NOTE: EVERYTHING I WROTE BELOW ARE MY OPINIONS AND REFLECT MY EXPERIENCE IN ACADEMIA (IN THE UK) – AT THE TIME OF WRITING. THEREFORE, THEY PROBABLY WILL NOT APPLY TO YOU. ALSO, PLEASE READ FROM START TO FINISH (INCL. FOOTNOTES) BEFORE POSTING COMMENTS.

Very soon, I’ll be moving to the ‘Human Genetics’ team of Boehringer Ingelheim Pharma (BI; Biberach R&D Centre in South Germany) as a ‘Senior Scientist’. I therefore wanted to look back at my time in academia and share my suggestion and concerns with other PhD students and early-career researchers (ECRs). Any criticism mentioned here is aimed at UK-based (research-intensive) academic institutions and “the system” – and not at any of my past supervisors/colleagues. The below are also going to be views that I have shared in some of my blog posts (e.g. Calculating the worth of an academic; Guide to an academic career in the UK; Bring back the ‘philosophy’ in ‘Natural philosophy’; What is success? YOU know better!) and with my colleagues throughout the years – and not something that I am just mentioning after securing a dream (will elaborate below on why I called it a ‘dream’) job at BI. (NB: See ‘Addendum (23/12/21)’ section, reflecting on my first 4-5 months at BI’s Human Genetics team)

To do my time in academia justice, I’ll get the good things out of the way first: I’ve been doing research for >10 years in UK-based academic institutions – first as a PhD student (Univ. of Bristol 2012-2015), then as a (Sn.) Postdoctoral Research Associate (2015-19 Univ. of Leicester; 2019-2021 Univ. of Cambridge) – and enjoyed almost every second of my time here. I met many world-class scientists but also great personalities whose memories and the things I learned from them will remain with me for the rest of my life. I was lucky to have had supervisors who also gave me the space and time to develop myself and I’d like to think I took good advantage of this. I also got to (i) publish quite a few papers I will always be proud about and (ii) travel to the US and many countries in Europe thanks to funding provided for academic conferences and, needless to say, none of them would have been possible without (4-year PhD) funding from the Medical Research Council (MRC UK) or support of my PhD/postdoc supervisors and colleagues. My time in the beautiful cities of Leicester (see: Life in Leicester), Bristol, and Cambridge was enjoyable too! I therefore would recommend any prospective scientist/researcher to spend at least some time as a ‘Postdoc’ in a research intensive UK-based university.

On top of all this, if you were to ask me 5 years ago, I would have said “I see myself staying in academia for the rest of my life” as I viewed my job as being paid for doing a ‘hobby’ – which was doing research, constantly learning, and rubbing shoulders with brilliant scientists. However, things started to change when I became a father towards the end of 2018, and I slowly began to have a change of heart about working in academia due to the well-known problems of fixed-term contracts/lack of permanent job opportunities, relatively poor* salaries compared to the private sector, and the many hurdles (incl. high workload) you need to overcome if you want to move a tiny bit up the ladder. The only thing keeping me going was my ideals of producing impactful science, my colleagues, and the possibility of pursuing my own ideas (and having PhD students). No one needs my acknowledgement to learn that there is ‘cutting-edge’ and potentially very impactful science being done at universities but the meaning of ‘impact’ for me changed during the COVID-19 pandemic when I was sat at home working on projects which I felt didn’t have much immediate impact and probably will not have much impact in the future either – and if they did, I probably would not be involved in the process as an ECR. On top of this, many of the (mostly COVID-19, and academia-related) analyses I was sharing on my Twitter page and blog were being read by tens of thousands. I was also heavily involved with the crowdfunding campaign of a one-year-old spinal muscular atrophy (type-1) patient (see tweet and news article). And these were both eye-opening and thought provoking! So the problems that I ignored or brushed under the carpet when I was a single, very early-career researcher were suddenly too big to ignore, and enduring through fixed-term jobs, relatively low pay packages* and a steep hierarchy (i.e. much more ‘status’ oriented than ideal) was just not worth it.

One of my biggest disappointments was not being able to move to Cambridge with my family because (i) Cambridge is very expensive relative to Leicester, and (ii) Univ. of Cambridge doesn’t pay their ECRs accordingly – mind you, I was being paid the equivalent of a (starting) ‘Lecturer’ post at the University’s pay scales (Point 49; see ‘Single Salary Spine’), so many of my colleagues were being paid less than myself.


There was also the issue of not having enough ‘independence’ as an ECR to work on different projects that excited me. As a ‘postdoc’, my priority had to be my supervisor’s projects/ideas. If I wanted to pursue my own projects, I had to bring my own salary via fellowship/grant applications – even those would have to be tailored towards the priorities of the funding bodies. Applying for grants/fellowships is not something I like or I’m trained for but I did try… I submitted three (one grant and two fellowship) applications and made it to the interview/final stage every time, however they were all ultimately rejected mostly because I “was not an expert on that respective disease” or “was too ambitious/couldn’t do all these in 3 (or 5) years”. I guess I also laid all my cards on the table and didn’t hide the fact that I was a proud ‘generalist’** and was never going to be a specialist as I am just too curious (and unwilling) to be working on a single disease or method. In addition to these, I had also co-applied (with a Lecturer colleague in the Arts dept. where we had to submit quite a few documents and a short video) for a very small grant (of ~£6000) to organise a conference to discuss the problems of asylum seekers/refugees in the UK, but it was rejected for strange reasons. I acknowledge that there is an element of luck involved and on another day with another panel, I may have been awarded but these rejections were also eye openers. (NB: I believe the ‘all-or-nothing’ nature of fellowship/grant applications should be revised as a colossal amount of researchers’ time and effort – and therefore taxpayers’ money – is being wasted)

But – in line with the story (of the Chinese farmer) I shared at the start – I am now happy that they didn’t work out as it probably would have meant I stayed in academia for longer (i.e. until the end of my fellowship period). I always took the ‘doing my best and not worrying about the outcome‘ approach and this has proven to be a good strategy for me so far.

Although unhappy with the way ‘the system’ took advantage of ECRs, I did try and “play by rules” to ramp up my CV and network by applying to become a ‘Non-stipendiary Junior Research Fellow’ at one of the colleges of the Univ. of Cambridge to increase my chances of securing a permanent lecturer post at a high-calibre university. Although I enjoy teaching and think I am good at explaining concepts, the main reason for applying was to add more teaching experience in my CV and secondly, to be more involved with the community of students and ECRs in Cambridge – which I did not have a chance to do much, mostly as I and my wife decided not to move to Cambridge from Leicester for the reasons mentioned above (underneath the first figure). I made a solid application and got to the interview stage. I thought the interview panel would be delighted to see someone like me who has a relatively good academic CV for an ECR (see my CV) but also does sports, has his own podcast, who tried to be active on social media (I had more followers than the college on Twitter – although they’re very active), who writes highly read blogs (some of my blog posts are read and shared by tens of thousands), led many student groups (incl. the President of Turkish Society at the Univ. of Bristol and Leicester) etc. to join their ‘guild’ but I was very surprised to receive a rejection email a couple of weeks later. I was going to work there for free, but it seems like they didn’t value my skills at all and that there were at least 5 other people who they thought were going to contribute to the College’s environment more than me. This was another eye-opener: Academia is full of (highly talented) ECRs who are just happy to do things for free for the sake of adding stuff to their CV and I realised I was about to do the same. I remember thinking “I dodged a bullet there” – I decided it just wasn’t worth fighting/competing over these things. I knew now that I had to explore options outside of academia more assertively as I could see clearer that universities and the senior members who helped build this system were just taking advantage of ECRs’ idealism and ambitions but also desperation. (BTW: I find it astonishing that non-stipendiary fellowships in Cambridge are even a thing. They state that they don’t expect much from their fellows but they clearly do)

I then shared a 1-page CV in certain job recruitment sites to see what was out there for me and I was surprised to see how valuable* some of my transferable skills were to businesses in different sectors. I had many interviews and pre-interview chats with agents and potential employers (incl. Pharma, other private sectors, and public sector) in the last 6 months but only one ticked all the boxes for me: this ‘Senior scientist’ role at the Human Genetics team of BI – who valued my versatility and expertise in various fields***. Thus, I took time out to fully concentrate on the process and prepared well. I had to go through five interview stages, including an hour-long presentation to a group of experts from different fields, before I was offered the post. Throughout the process I also saw that many of my prospective colleagues at BI had seen the abovementioned problems earlier than I did and made the move. They were all very happy, with many working, and hoping to stay, in the company for a long time. I should also mention I had a Lecturer job lined up at the Univ. of Manchester**** too but the opportunity to work for BI’s ‘Human Genetics’ team was too good to refuse.

I didn’t mean this post to be this long so I’ll stop here. To sum up, I am proud of the things I’ve achieved and the friends I’ve made along the way – and if I was to go back, I wouldn’t change anything – but I believe it is the right time for me to leave academia. I think I’ve been a good servant to the groups I worked in and tried to give all I could. Simultaneously, I grew a lot as a scientist but also as a person – and this was almost all down to the environment we were provided at the universities I worked in. But having reached this stage in my life and career, I now think that (UK) universities don’t treat us (i.e. ECRs) in the right way and provide us with the necessary tools or the empathy to take the next step. I don’t see this changing in the near future either because of the fierce job market. Universities are somehow getting away with it – at least for now. This is not to say other sectors are too different in general but I would strongly recommend exploring the job market outside of academia. You may stumble on a recruiter like BI and a post like the one I have been offered, which matches my skill set and ambitions but also pay well so I can live a decent life with my family – without having to live tens of miles away from my office.

Let me re-iterate before I finish: What I wrote above will most probably not apply to you as I (i) am a UK-based academic/researcher, (ii) am an early-career researcher in a field which also has a strong computational/programming and statistics component – so I have a lot of easy-to-sell transferable skills to the Pharma companies/private sector, (iii) am a ‘generalist’** rather than a ‘specialist’ – so I’m a person major funding bodies currently aren’t really too keen on, (iv) don’t have rich parents or much savings, and am married (to a PhD student) and have a son to look after – and thus, salary*****, living in a decent house/neighbourhood and spending time with my family is an important issue, and (v) am an impatient idealist, who wants to see his research have impact – and as soon as possible. I am also in a position that I can make a move to another country with my family.


Footnotes:

*Contractor jobs usually offer much better pay packages than permanent jobs in the ‘data science’ field e.g. as soon I as put my CV on the market as a ‘health data scientist’, I got contacted by a lot of agents who could find me short-term (3-12 months mainly) contracts with very good pay packages. Just to give one example of the salaries offered, there was one agent who in an apologetic tone said: “I know this is not very good for someone like you but we currently offer £400 a day to our contractors but I can push it to £450 for you.”this is ~3x the daily rate of my salary at the Univ. of Cambridge!

**I’ve always been involved in top groups and ‘cutting-edge’ projects so the jump from academia to Pharma in terms of research quality is not going to be too steep but the possibility of being directly involved in the process of a drug target that we identify go through the stages and maybe even become a drug that’s served to patients is not there for a (32 year old) ECR in academia – maybe, when I’m 45-50 years old. I also like the “skin in the game” and “all in the same boat” mentality in many Pharma/BI posts, which I do not see in academia. The current system incentivises people to be very individualistic in academia; and the repetitive and long process of publishing (at least partially) ‘rushed’ papers to lay claim to a potential discovery are things that have always bothered me. I don’t see how I can further improve myself personally and as a scientist as I don’t think my skills were anywhere near fully appreciated there – the system almost solely cares about publishing more and more papers, and bringing in funding. I have many ‘junior’ and ‘senior’ friends/colleagues who have made the transition from academia to Pharma (incl. Roche, NovoNordisk, GSK, AZ, Pfizer) and virtually all of them are happy to have moved on.

***As you can also see from my Google Scholar profile (and CV), I have worked on different diseases/traits and concepts/methods within the fields of medical genetics (e.g. rare diseases such as primary ciliary dyskinesia and Papillon-Lefevre syndrome), genetic epidemiology (e.g. common diseases such as type-2 diabetes and chronic obstructive pulmonary disease, and related traits such as smoking behaviour and blood pressure), (pure) epidemiology (COVID-19 studies), population genetics (Y-DNA & mtDNA haplogroup studies), and statistical genetics (e.g. LD Hub, HAPRAP) – and this is generally not seen as a ‘good sign’ (even when I’ve published papers in some of the most respectable journals in the respective fields as first/equal-first/prominent author) by some ‘senior academics’ (who review your grant/fellowship applications, and papers submitted to respectable journals) as many have spent their entire careers on a single disease, and sometimes on a single/few genes. It doesn’t mean they are right, but they usually make the final decision – and some like to act as gate keepers.

****I applied to the Univ. of Manchester post in case I would not get the BI job but also because it was a nice opportunity to work at a top university/department with high quality students and great scientists. They were also happy to pay me at the higher end of the ‘Lecturer’ salary scale. I believe I would have been a good lecturer and colleague but I just did not see myself in (UK) academia in its current state.

*****Although I – with my wife and son – was living in a nice neighbourhood and house in Leicester (renting of course!), due to my son’s expenses incl. a private nanny for a couple of days a week as my wife was also busy like me (small matter of writing her PhD thesis!), we were basically living paycheck to paycheck – and that was hard. When there were unexpected expenses, we used my wife’s (small amount of) savings, then asked my brother to help out financially – and that was hard too. It was almost impossible to fully concentrate on my research as I was always on the lookout for investment opportunities using the small amount of money I had on the side. At one point, I even contemplated doing casual work to earn a bit of cash on the side. Needless to say, I am very disappointed with the pay packages in academia – at least a stratified approach according to field, (transferable) skillset, and marriage/child status/other circumstances should be considered in my opinion. I also think, universities should at least provide guidance on solid investment (incl. mortgage) opportunities to their ECRs, so they can potentially earn or save a bit more. I can’t say much about my salary but it is a senior and permanent post, and my pay package also includes many of the perks of academia (e.g. >30 days of paid annual leave, flexible working hours, conference/travel allowance).


Couple of tweets – in addition to the blog posts I shared above – where I complain openly about the state of (UK-based) academia:

1- I don’t know how “no/limited feedback” has been normalised in academia:

2- I think science communication is as important as the papers we publish:

3- Publishing papers for the sake of publishing and inflating h-indexes:


Addendum (23/12/21) Reflecting on my first 4 months at BI’s Human Genetics team:

I was going to write a piece later but decided to add to this post now as I have been/am being invited to many ‘academia v industry/pharma‘ workshops/talks and saw that there is a lot of interest in this subject. I cannot properly respond to all emails or accept all invitations, thus would like to direct people here when needed…

A quick summary of what I’m doing: I’m a ‘Senior Scientist’ in the relatively newly established Human Genetics team of BI – and we’re located at the International Research Centre in the beautiful city of Biberach an der Riss in South Germany. As the Human Genetics team, we’re currently building analysis pipelines to make use of the huge amount of human genetics, proteomics and transcriptomics data that’s available to (in)validate the company’s portfolio of drugs (see below video for details).

A short primer on how I spend my days in the Human Genetics team of Boehringer Ingelheim: Leveraging human genetics data to guide drug target validation – Mesut Erzurumluoglu (Respiration/Solunum conference on 31/10/21)

If I say a few words about BI – which I didn’t know before I joined: BI one of the largest family-owned companies in the world with >20 billion euros revenue per year and >50k employees all around the world of which >8k are researchers (largest R&D centre is in Biberach an der Riss, where we’re also located) – so the company and the Boehringer/Von Baumbach family value R&D a lot. Some family members also attend research days organised within the company – which I find very encouraging as an employee but also a scientist at heart!

The other exciting thing for me is that the company’s currently going through a phase of massive expansion in ‘data driven drug target validation’, so the Comp. Bio/Human Genetics department is getting a lot of investment and are going to hire a lot of people in the near future – and I’m very happy to be involved in this process too.

To get back to my views of ‘working for BI v in academia’, I’ve made a summary table below which compares my experience as a Senior Scientist in BI and my time as an ECR/(Sn.) Postdoc/(Prospective) Lecturer in UK academia. I’ve highlighted in bold where I think one side better was than the other for me.

I believe the above rows are self-explanatory except maybe the bottom 4 rows – so I will provide some details here: (i) I feel like we’re ‘all in the same boat’ in my current team as we – as a group – have certain targets that we need to hit, so any success/breakthrough by any of the team members alleviates the pressure on all of us. This is also true of any success within the company. (ii) Re the next point/row, I just want to give one example: I have seen many papers be published in very high-impact journals by ‘top names’, which would not have made it past the ‘top names’ themselves (as reviewers) had the paper been written by some other group. Most of us also don’t have any editor friends who we can write to so that our ‘desk rejection’ at a high-impact journals is reviewed. The struggle for funding is even worse and I think life’s too short to be spending months on a fellowship or grant application, which is usually rejected for non-research related reasons (e.g. competition, timelines, priorities). (iii) We’re not allowed to work on Sundays at BI, and emails sent to others on Saturdays and after work hours is genuinely discouraged. (iv) Last row: We’re encouraged to produce good science and analysis pipelines by the senior management at BI rather than be in competition with colleagues to be the ‘first’ at something. In contrast, many papers in academia will be published in high-impact journals and be cited by others because they were the ‘first’ and not because they did a good job of strengthening their finding(s) via different lines of evidence. They do not lose anything if this ‘new and shiny’ finding turns out to be just a meaningless correlation 5-6 years down the line (i.e. there’s no “skin in the game”; even worse, they will have collected their grants and awards by then).

I also want to mention that career progression in UK academia is too slow for my liking (see below figure). I do not want to be treated as an ECR and living ‘paycheck to paycheck’ until I’m 50 – again, I feel like life is too short for this. This is why I wanted to move to a group where I would be respected more but also earning more – so that I can provide a good life for my family whilst fully concentrating on my/the team’s ‘cutting-edge’ research.

I always judged my ‘value’ at a place by adding how much I was earning and learning there. I was very happy during my PhD and first few years as a postdoc as I was learning a lot (from top scientists, attending conferences, giving talks, being provided the time to explore) and had a good salary/scholarship for a person who is single and <30 years of age. Unfortunately, for me, the increase in this regard was just not steep enough after this period. This feeling didn’t change much even after I secured a Lecturer post at the Univ. of Manchester – I just could not beg funders and apply for grants every year until I die. At BI, in addition to a very good salary, I’m also learning a lot from the different groups we are interacting with (e.g. wet-lab researchers/CRISPR screens, drug target research in different disease areas such as respiratory, immunology, oncology, and cardio-metabolic diseases) whilst also taking part in ‘cutting-edge’ research. There are also internal funds to explore your own ideas and a separate programme called ‘Research Beyond Borders’, which is dedicated to looking into other diseases which do not fit the main programmes.

To finish, I again re-iterate that it would be wise for a talented postdoc with data science and statistical skills to have a look around while they’re still comfortable in their current post (i.e. still have >12 months contract). If you have experience working with clinical and genetic data, then Pharma and Biotech companies would also be very interested in you.

I hope this post is of help, but feel free to contact me if you have specific questions that are not answered here.


Addendum (23/12/23) Reflecting on my first ~2.5 years at BI’s Human Genetics team:

Still happy. Family’s happy here. South Germany is very good for families: Very safe. My son’s kindergarten is great; Biberach and surrounding area is great. So much to see and learn.

Happy with the research I’m doing, things I’ve learned/learning, and my impact in the drug target development process at BI.

Also check out our preprint on structural variants – a valuable resource, openly shared with the research community (Note: I had encouraged Boris Noyvert to join our team and now we’ve published this preprint together):

Noyvert B, Erzurumluoglu AM, Drichel D, Omland S, Andlauer TFM et al. 2023. Imputation of structural variants using a multi-ancestry long-read sequencing panel enables identification of disease associations: https://www.medrxiv.org/content/10.1101/2023.12.20.23300308v1

Tweetorial:

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Many of today’s scientists (incl. myself a lot of the time) have probably lost touch with some of the central tenets of being a scientist – instead titles, number of published papers and grant money brought in becoming more important than the societal impact of their publications and how much they contributed to human knowledge. A shoddy paper published in Nature/Science/Cell (especially if cited/talked about a lot) carries far more weight than a solid paper in a less glamorous journal. An academic who brings in grant money – doesn’t matter if he/she wastes it on shoddy or average research – is far more important (i.e. they will be promoted and bring in further funding easier as they already brought in some before) than one who chooses to concentrate on producing solid research but struggles to bring in money e.g. due to a lack of funding in their specific field or publishing papers in non-glamorous journals due to ‘non-exciting’ results as they didn’t add a spin to their conclusions (click here for other examples). Some of the papers published in prestigious journals in my field would not have been accepted if the senior authors of the same papers were the reviewers – many seem to apply a less stringent criteria to their own papers. The relationship between editors and some senior scientists is also opaque which is ultimately damaging to science. Image source: naturalphilosophy.org

Hell for academics and researchers (NB: The list is loosely ordered and is not an exhaustive one). Of course, inspired by Dante’s Nine levels/layers/circles of Hell

A few months ago, I spent almost a week trying to replicate a published “causal” association which had received >500 citations in the last 5 years. My aim was to provide a better effect estimate and to do this, I used two different datasets, one with similar and another with a larger sample size. However, both of my analyses returned null results (i.e. no effect of exposure on outcome). Positive controls were carried out to make sure the analysis pipeline was working correctly. Ultimately, I moved on to other ‘more interesting’ projects as there was no point spending time writing a paper that was probably going to end up in a ‘not-so-prestigious’ journal and never going to get >500 citations or be weighted heavily when I apply for grants/fellowships.

Consequently, inadvertently I contributed to publication bias on this issue – and no other analyses on the subject matter were published since the original publication, so I am sure others have found similar results and chose not to publish.

State of academia (very generally speaking): Really talented and successful people working like slaves for unimportant academic titles and average salaries. What’s worse is that the job market is so fierce that most are perfectly happy(!) to just get on with their ‘jobs and do what they’ve always been doing (Note: this is my first attempt at drawing using Paint 🙂 )

However, I have changed my mind about publishing null/negative results after encountering Russell, Wittgenstein and others’ long debates on proving ‘negative’ truths/facts (and in a nutshell, how hard it is to prove negatives – which should make it especially important to publish conclusive null findings). These giants of philosophy thought it was an important issue and spent years structuring their ideas but here I am, not seeing my conclusive null results worthy of publication. I (and the others who found similar results) should have at least published a preprint to right a wrong – and this sentiment doesn’t just apply to the scientific literature. I also think academics should spend some time on social media to issue corrections to common misconceptions in the general public.

This also got me thinking about my university education: I was not taught any philosophy other than bioethics during my undergraduate course in biological sciences (specialising in Genetics in the final year). I am now more convinced than ever that ‘relevant’ philosophy (e.g. importance of publishing all results, taking a step back and revisiting what ‘knowledge’ is and how to attain ‘truth’, how to construct an argument1, critical thinking/logical fallacies, what is an academic’s intellectual responsibility?) should be embedded and mandatory in all ‘natural science’ courses. This way, I believe future scientists and journal editors would appreciate the importance of publishing negative/null results more and allow well-done experiments to be published in ‘prestigious’ journals more. This way, hopefully, less published research findings are going to be false2.

References/Further reading:

  1. Think Again I: How to Understand Arguments (Coursera MOOC)
  2. Ioannidis JPA. Why Most Published Research Findings Are False. PLoS Med. 2(8): e124 (2015)
  3. How Life Sciences Actually Work: Findings of a Year-Long Investigation (Blog post)
  4. An interesting Quora discussion: Why do some intelligent people lose all interest in academia?
  5. Calculating the ‘worth’ of an academic (Blog post)
A gross generalisation but unfortunately there is some truth behind this table – and it’s not even a comprehensive list (e.g. gatekeepers, cherry picking of results). Incentives need to change asap – and more idealists are needed in academic circles!

*the title comes from the fact that today’s natural scientists would have been called ‘natural philosophers’ back in the day

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Ne en güçlü, ne de en zeki olanlar hayatta kalır… Hayatta kalanlar değişime en çok adapte olabilenlerdir.” – Charles Darwin’in söylediği iddia edilir


Cambridge Üniversitesi’ne nasıl kabul aldın?

Twitter’da gördüm sanırım: “Aynı soru sana üç defa sorulduysa bir blog yazısı yazma vakti gelmiştir”e benzer bir cümleydi. Ben de “Cambridge Üniversitesi’ne nasıl kabul aldın?” ve benzeri sorularla pek çok defa karşılaştıktan sonra birşeyler karalamaya karar verdim. Leicester Üniversitesi’nde çalışırken bunun onda biri dahi sorulmamıştı 😉

Doktora öğrencilerine, doktorayı yeni bitirenlere ve akademik kariyer düşünen gençlere yönelik uzun bir doküman hazırladım. Az da olsa ingilizce terimler kullandım ama merak eden herkes okuyabilsin diye elimden geldikçe azaltmaya çalıştım (Not: iyi derecede ingilizce bilmeyenlerin iyi üniversitelere girmesi, hasbel-kader girdiyse de oralarda tutunması zor).

Okuyacağınız herşey benim şahsi düşüncelerim ve hiçbirine katılmak zorunda değilsiniz. Eminim yazdıklarımda hatalar ve eksikler olacaktır; bunları da bana bildirirseniz dökümanı hep beraber geliştirmiş oluruz. Katkıda bulunanlara da bir şekilde değineceğim. Şimdiden teşekkürler!

Darwin’e atfedilen yukarıda paylaştığım hakikat dolu sözle bir bağlantı kuracak olursam, evet, bir akademisyen için çok akıllı/zeki olmak bir avantajdır. Ama oyunun kurallarını (örneğin ‘arkadaşlarım/hocalarımla aramı nasıl iyi tutarım?‘, ‘iyi makale nasıl yazılır?‘, ‘nasıl fon getiririm?‘i) öğrenmek ve onlara göre adapte olmak da en az o kadar önemli – özellikle akademide oldugu gibi ‘oyun’un kuralları devamlı degişiyorsa… İşin bu kısımlarına da vakit harcayın.

Aşağıdaki dökümanda “Doktora sürecinde nelere dikkat etmeliyim?”, İngiltere’de akademik kariyer opsiyonları, “CV ve ‘Personal statement’ nasıl hazırlanır?“, ‘mülakat anı, öncesi ve sonrası neler yapmalıyım?‘, tez yazarken dikkat edilecekler, makale yazarken dikkat edilecekler ve prosedür, “Hocanızla ilişkiniz nasıl olmalı?” gibi konularda bilgiler ve tavsiyelerim bulunuyor. Umarım yardımcı olur. İlgileneceğini düşündüğünüz arkadaşlarınıza da yollarsanız sevinirim.

Ek olarak ilgili video ve tweetler:

Manisa Celal Bayar Üniversitesi Biyomühendislik ve Elektronik Mühendisliği lisans öğrencilerine sunum (13 Mayıs 2020)
Brit-Iş TV’den Ergin Balabeyoğlu’na verdiğim kısa roportaj
Rafşan Çelik’le Cambridge Üniversitesinde Akademisyen Olmak ve İngiltere’de Yaşam, Kültür ve Akademik Hayat uzerine (Instagram üzerinden*) söyleşi yaptık (3:38’de başlıyor).


Ingiltere’de üniversiteler – genel kurallara uyma dışında – devletten bağımsızdır. Örneğin hepsi kendi fonunu kendi bulur, yani büyük bir şirket gibi işlerler. Fakat en büyük fon 7 senede bir devletten gelir – üniversitelerin başarı seviyesine göre. Bu da onunla ilgili bir Tweet zinciri
Kıymetli Prof. Hikmet Geçkil Hocamın da bu dokümanı tavsiye ettiğini gördüm ve mutlu oldum. Umarım faydalı olmuştur

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Difference between the lung of a COPD patient and an unaffected one. Image taken from NHLBI website (click on image to access the source)

Difference between the lung of a COPD patient and an unaffected one. Image taken from the NHLBI website (one of the leading institutes in providing information on various diseases; click on image to access the source)

Many of us will either suffer or have a relative/friend who suffers from a disease called Chronic Obstructive Pulmonary Disease (COPD, click on link for details) which is a progressive respiratory disease characterised by decreasing lung function (struggling to inhale/exhale air, irreversible airflow obstruction), very likely accompanied by chronic infections. COPD has a prevalence of over 2% in the UK population (corresponding to approx. 1 million in the UK, probably a lower bound estimate due to many undiagnosed cases; this figure is approx. 16 million in the USA) and is currently the third biggest killer in the world (only behind cancers and heart-related diseases) – costing the lives of millions (in the USA alone, number of deaths attributed to COPD is over 100 thousand); and the health services, billions of pounds.

Contrary to the well-known genetic disorders such as Cystic Fibrosis and Huntington’s disease, which are diseases caused entirely by a person’s genetic makeup and caused by mutations in a single gene, COPD is a (very!) complex disease with many genes and environmental factors (e.g. smoking, pollutants) contributing to the development/progression of the disease. This complexity makes it much harder to dissect the causes and find potential (genetic) targets for cures or therapies. However, we do know that smoking is by far the biggest risk factor with up to 90% of those who go on to develop clinically significant COPD being smokers. But only a minority (<25%) of all smokers develop COPD, indicating the strong role genetics can play in the progression of this disorder. Also not all COPD patients are smokers (up to 25% in some populations), indicating that – at least in some patients – genetics can play a rather determining role. I must stress that all the statistics I provide here can vary considerably from population to population due to different lifestyles and genetic backgrounds.

Genetic_epidemiology_genetics_mesut_erzurumluoglu

I – together with a large group of collaborators – search for genetic predictors of lung function, which helps us to identify which individuals are more likely to develop the disease and potentially understand the underlying biology/pathology of respiratory diseases such as COPD and asthma, and related traits such as smoking behaviour. To do this, we carry out what is called a genome-wide association study (GWAS, click on link for details), where we obtain the genetic data (millions of data points) from tens of thousands of COPD (or asthma) patients and ‘controls’ (people with normal lung function). To ensure that our results are not biased by different ethnicities, life styles and related individuals, we collect all the relevant information about the participants and make sure that we control for them in the statistical models that we use. GWASs have been extremely successful in the identification of successful targets for other diseases and have led to the field of Genetic Epidemiology (GE, click on link for details) to come to the fore of population-based medicine. GE requires extensive understanding of Statistics (needed to make sense of the very large datasets), Bioinformatics (application of computer software to the management of large biological data), Programming (needed to change data formats, manage very large data), Genetics (needed for interpretation of results) and Epidemiology (branch of medicine which deals with how often diseases occur in different groups of people, and why); thus requires inter-disciplinary collaborations.

GWAS results are traditionally presented with a Manhattan plot (due to its resemblance of the city's skyline) where the genetic variants corresponding to the dots above the top grey line (representing P values less than 5e-7 i.e. 0.0000005) are usually followed up with additional studies to validate their plausibility. Image taken from Wikipedia (click on image to access source)

GWAS results are traditionally presented with a Manhattan plot (due to its resemblance of the city’s skyline) where the genetic variants corresponding to the dots above the top grey line (representing P-values less than 5e-8 i.e. 0.00000005) are usually followed up with additional studies to validate their plausibility. Image taken from Wikipedia (click on image to access source)

The inferences we make from these studies can shed light in to which genes and biological pathways play key roles in causing COPD. We then follow up these newly identified genes and pathways to analyse whether there are molecules which could be used to target these and be potential drugs for treating COPD patients. Our results can be of immense help to Pharmaceutical companies (and ultimately to patients), as many clinical trials initiated without genetic line of evidence have failed, costing the public and these companies billions of pounds.

As smoking is the biggest risk factor for respiratory diseases like COPD, I am – also with the contribution of many collaborators – in the process of analysing whether some people are more likely to start smoking, stop after starting, and smoke more than usual when they start smoking. The results can have huge implications as many people struggle to stop smoking, and when they do, research suggests that up to 90% (figure differs between populations) of them start to smoke again within the first year after quitting. Smoking is not only a huge contributor to the risk of developing COPD, but also to lung (biggest killer amongst all cancers), mouth, throat, kidney, liver, pancreas, stomach and colon cancer (not an exhaustive list). In the UK alone, these cancers cause the slow and painful death of tens of thousands, alongside a huge psychological and financial burden on the families and public resources.

The “lung” and the short of it (stealing a phrase thought up by my colleagues at the University of Leicester, click on link to see who they are) is that COPD is a disease that is going to affect many of us, and any useful finding which leads to cures and/or therapies could increase the life years of COPD patients and affect the lives of thousands of people directly, and millions indirectly (e.g. families of COPD sufferers, cost to the NHS). Finding targets to help people stop smoking can potentially have even bigger implications as many continue to smoke, despite huge efforts and funding allocated to smoking prevention and cessation.

A nice TED talk about the world of Data science and Genetic Epidemiology

Addition to post (09/02/17): A Circos plot presenting results from our latest lung function GWAS (Wain et al, 2017; Nature Genetics) was shortlisted (title: Breathtaking genes) and displayed in the Images of Research exhibition (9th Feb 2017) organised by the University of Leicester

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