Life after FTTF

In [13]:
from IPython.display import Image
Image("https://physics.fjfi.cvut.cz/images/comprofiler/667_54ef5fa733094.jpg", width=200, height=500)
Out[13]:

Personal Data

In [12]:
{'name':'Adam','surname':'Seman','school': 'Czech Technical University','specialization': 'Physics and technology of thermonuclear fusion','date of final exam':'16-02-2017','thesis':'COMPASS tokamak experiments support by simulations'}
Out[12]:
{'date of final exam': '16-02-2017',
 'name': 'Adam',
 'school': 'Czech Technical University',
 'specialization': 'Physics and technology of thermonuclear fusion',
 'surname': 'Seman',
 'thesis': 'COMPASS tokamak experiments support by simulations'}

What after ?

  • PHD ?? : still considering
  • started working outside academic sector with perspective of analytic work or programming

First experience: Lottery games at EVONA

In [15]:
from IPython.display import Image
Image("https://www.evona.sk/wp-content/uploads/2019/01/png-evo.png", width=200, height=500)
Out[15]:
  • create simulation of lottery game playing
In [12]:
import numpy as np
possible_numbers = np.arange(1,8)

def random_choice(n,M):
    m = len(M)
    N = []
    for i in range(n):
        m = len(M)
        j = np.random.randint(m)
        N.append(M[j])
        M = M[M != M[j]]
    return np.array(N)

def win_consideration(bet,draw):
    return np.all(np.in1d(bet,draw))*5

draw = random_choice(5,possible_numbers)

payins = np.ones(10000)
payouts = np.array([win_consideration(random_choice(5,possible_numbers),draw) for i in range(10000)])

import matplotlib.pyplot as plt
fix, axes = plt.subplots() 

axes.plot(np.cumsum(payouts)/np.cumsum(payins))
axes.plot(5*float(5*4*3*2)/(7*6*5*4*3)*np.ones(10000))
Out[12]:
[<matplotlib.lines.Line2D at 0xb5d3ba8>]

Second experience: Theoretical physics at GA DRILLING

In [27]:
from IPython.display import Image
Image("https://www.gadrilling.com/assets/img/header/home-drill.png", width=200, height=500)
Out[27]:
  • great look at first sight : plasma, geothermal applications, oil and gas applications
  • marketing is dangerous

Data analysis

In [28]:
from IPython.display import Image
Image("C:\Users\iveta\OneDrive\Pictures\Experiment_Mykola_2018-01-23_13-00.png", width=700, height=500)
Out[28]:

Simulations - Python, FEMM, OpenFOAM, ANSYS

In [30]:
from IPython.display import Image
Image("C:\Users\iveta\OneDrive\Pictures\magnetic_field.png", width=400, height=500)
Out[30]:
In [31]:
from IPython.display import Image
Image("C:\Users\iveta\OneDrive\Pictures\ecm1.png", width=400, height=500)
Out[31]:

Today: Python Developer at ERNI

In [40]:
from IPython.display import Image
Image("C:\Users\iveta\OneDrive\Pictures\logo.png", width=200, height=500)
Out[40]:
  • on project for computing financial derivatives based on stochastic differential equation: $$dS=r S dt +\sigma S dW$$
In [6]:
fix, axes = plt.subplots() 

S0 = 10
r = 0.0
sigma = 0.1
t = np.linspace(0,10000)
S = np.zeros_like(t)
S[0] = S0
for i in range(500):
    dW = np.random.normal(0,1,size = 10000)
    for i,dt in enumerate(np.diff(t)):
        dS = r*dt*S[i] + sigma*S[i]*dW[i]
        S[i+1] = S[i] + dS

    axes.plot(t,S)
In [ ]: